from google.colab import drive
drive.mount('/content/drive')
%cd /content/drive/MyDrive/HW2
Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount("/content/drive", force_remount=True).
/content/drive/MyDrive/HW2
We import the necessary libraries and set the dataset paths.
import pandas as pd
import json
import numpy as np
import matplotlib.pyplot as plt
import datetime
authors_set = 'lighter_authors.json'
books_set = 'lighter_books.json'
Loading the Authors Dataset
# Chunk size
chunk_size = 50000
# Initialize an empty list to store chunks
authors = pd.DataFrame()
# Loop through each chunk and append it to the result dataframe
for chunk in pd.read_json(authors_set, lines=True, chunksize=chunk_size):
# Select only the required columns from the chunk
#selected_chunk = chunk[["name", "gender", "fans_count", "average_rating", "ratings_count", "text_reviews_count", "works_count"]]
# Append the selected chunk to the list
authors = pd.concat([authors, chunk], ignore_index=True)
authors.head(5)
| ratings_count | average_rating | text_reviews_count | work_ids | book_ids | works_count | id | name | gender | image_url | about | fans_count | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2862064 | 4.19 | 62681 | [3078186, 135328, 1877624, 74123, 3078120, 104... | [386162, 13, 8695, 8694, 6091075, 365, 569429,... | 106 | 4 | Douglas Adams | male | https://images.gr-assets.com/authors/159137433... | Douglas Noël Adams was an English author, comi... | 19826 |
| 1 | 1417316 | 4.02 | 84176 | [613469, 2305997, 940892, 2611786, 7800569, 31... | [9791, 21, 28, 24, 7507825, 27, 10538, 25, 26,... | 75 | 7 | Bill Bryson | male | https://images.gr-assets.com/authors/157859752... | William McGuire "Bill" Bryson, OBE, FRS was bo... | 16144 |
| 2 | 56159 | 4.53 | 352 | [17150, 808427, 20487307, 90550, 25460625, 171... | [349254, 15222, 14833682, 15221, 18126815, 152... | 14 | 10 | Jude Fisher | female | https://images.gr-assets.com/authors/141145711... | Jude Fisher is the pseudonym for <a href="http... | 60 |
| 3 | 3302 | 3.79 | 480 | [4417, 14300808, 14780, 3796968, 44703121, 103... | [40, 9416484, 12482, 3753106, 26889789, 104764... | 45 | 12 | James Hamilton-Paterson | male | https://images.gr-assets.com/authors/127051738... | James Hamilton-Paterson's work has been transl... | 72 |
| 4 | 7979 | 3.60 | 772 | [13330815, 19109351, 42306244, 72694240, 26291... | [8466327, 15739968, 22756778, 51026133, 260451... | 61 | 14 | Mark Watson | male | https://images.gr-assets.com/authors/133175379... | Mark Andrew Watson (born 13 February 1980) is ... | 179 |
authors.describe()
| ratings_count | average_rating | text_reviews_count | works_count | id | fans_count | |
|---|---|---|---|---|---|---|
| count | 3.517670e+05 | 351767.000000 | 351767.000000 | 3.517670e+05 | 3.517670e+05 | 351767.000000 |
| mean | 4.770586e+03 | 3.651194 | 330.993243 | 2.593714e+01 | 7.751861e+06 | 111.615731 |
| std | 9.769395e+04 | 1.211482 | 3857.539191 | 3.066083e+03 | 6.578409e+06 | 2661.018139 |
| min | -4.100000e+01 | -31.000000 | 0.000000 | 0.000000e+00 | 4.000000e+00 | -33.000000 |
| 25% | 6.000000e+00 | 3.600000 | 1.000000 | 2.000000e+00 | 1.535315e+06 | 1.000000 |
| 50% | 3.900000e+01 | 3.950000 | 8.000000 | 6.000000e+00 | 6.470396e+06 | 4.000000 |
| 75% | 3.100000e+02 | 4.250000 | 53.000000 | 1.500000e+01 | 1.434041e+07 | 20.000000 |
| max | 2.700375e+07 | 5.000000 | 608956.000000 | 1.775176e+06 | 2.124802e+07 | 766035.000000 |
Data Cleaning on Authors
authors2 = authors
authors2.shape
(351767, 12)
authors[authors.apply(lambda x: len(x.work_ids)!=x.works_count, axis=1)].shape[0]
444
These 444 rows are junk rows because count of work does not match with the number of work ids listed. Hence we will discard these rows.
authors2=authors2[authors2.apply(lambda x: len(x.work_ids)==x.works_count, axis=1)]
authors2.describe()
| ratings_count | average_rating | text_reviews_count | works_count | id | fans_count | |
|---|---|---|---|---|---|---|
| count | 3.513230e+05 | 351323.000000 | 351323.000000 | 351323.000000 | 3.513230e+05 | 351323.000000 |
| mean | 4.484867e+03 | 3.650981 | 320.351201 | 16.279185 | 7.758528e+06 | 107.322885 |
| std | 9.136027e+04 | 1.211959 | 3641.125698 | 40.387565 | 6.578301e+06 | 2319.479591 |
| min | -4.100000e+01 | -31.000000 | 0.000000 | 0.000000 | 4.000000e+00 | -33.000000 |
| 25% | 6.000000e+00 | 3.600000 | 1.000000 | 2.000000 | 1.547222e+06 | 1.000000 |
| 50% | 3.900000e+01 | 3.950000 | 8.000000 | 6.000000 | 6.471876e+06 | 4.000000 |
| 75% | 3.080000e+02 | 4.250000 | 52.000000 | 15.000000 | 1.434526e+07 | 20.000000 |
| max | 2.700375e+07 | 5.000000 | 606373.000000 | 1511.000000 | 2.124802e+07 | 455358.000000 |
Looking at the negative minimum values of the numeric columns in this description, we decide to filter those out.
authors2.dropna(inplace=True)
<ipython-input-8-26e85020d60f>:1: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy authors2.dropna(inplace=True)
authors2 = authors2[(authors2[["fans_count", "average_rating", "ratings_count", "text_reviews_count", "works_count"]] >= 0).all(axis=1)]
authors2.describe()
| ratings_count | average_rating | text_reviews_count | works_count | id | fans_count | |
|---|---|---|---|---|---|---|
| count | 3.512960e+05 | 351296.000000 | 351296.000000 | 351296.000000 | 3.512960e+05 | 351296.000000 |
| mean | 4.485211e+03 | 3.651070 | 320.375586 | 16.280052 | 7.758450e+06 | 107.331498 |
| std | 9.136377e+04 | 1.210561 | 3641.264559 | 40.388956 | 6.578473e+06 | 2319.568516 |
| min | 0.000000e+00 | 0.000000 | 0.000000 | 0.000000 | 4.000000e+00 | 0.000000 |
| 25% | 6.000000e+00 | 3.600000 | 1.000000 | 2.000000 | 1.546958e+06 | 1.000000 |
| 50% | 3.900000e+01 | 3.950000 | 8.000000 | 6.000000 | 6.471733e+06 | 4.000000 |
| 75% | 3.080000e+02 | 4.250000 | 52.000000 | 15.000000 | 1.434546e+07 | 20.000000 |
| max | 2.700375e+07 | 5.000000 | 606373.000000 | 1511.000000 | 2.124802e+07 | 455358.000000 |
Now the description gives proper values for the minimum of the numeric columns.
min(authors2['work_ids'])
[]
The minimum of the work_ids column has returned empty list, we will clear this junk as well and we repeat this same technique for all other non numeric columns.
authors2=authors2[authors2.apply(lambda x: x.work_ids!=[] and x.book_ids!=[],axis=1)]
authors2[authors2['gender']==''].shape[0]
103237
As per this query, I got 103237 rows with no Gender of the author specified. To do a better analysis of the data, I am discarding these rows with no gender specified and saving it to another copy as authors3.
authors3=authors2[authors2['gender']!='']
authors3.shape[0]
248056
Loading the Books Dataset
# Chunk size
chunk_size = 50000
# Initialize an empty list to store chunks
books = pd.DataFrame()
# Loop through each chunk and append it to the result dataframe
for chunk in pd.read_json(books_set, lines=True, chunksize=chunk_size):
# Select only the required columns from the chunk
selected_chunk = chunk[["title", "num_pages", "language", "average_rating", "ratings_count","text_reviews_count", "author_name", "original_publication_date", "publication_date","format","series_id","series_name","series_position"]]
#selected_chunk = chunk[["original_publication_date"]]
# Append the selected chunk to the list
books = pd.concat([books, selected_chunk], ignore_index=True)
books.head(5)
| title | num_pages | language | average_rating | ratings_count | text_reviews_count | author_name | original_publication_date | publication_date | format | series_id | series_name | series_position | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Harry Potter and the Order of the Phoenix (Har... | 870 | eng | 4.50 | 2628006 | 44716 | J.K. Rowling | 2003-06-21 | 2004-09 | Paperback | 45175 | Harry Potter | 5 |
| 1 | Harry Potter and the Sorcerer's Stone (Harry P... | 309 | eng | 4.48 | 7377351 | 116930 | J.K. Rowling | 1997-06-26 | 2003-11-01 | Hardcover | 45175 | Harry Potter | 1 |
| 2 | Harry Potter and the Chamber of Secrets (Harry... | 352 | eng | 4.43 | 2855044 | 55286 | J.K. Rowling | 1998-07-02 | 2003-11-01 | Hardcover | 45175 | Harry Potter | 2 |
| 3 | Harry Potter and the Prisoner of Azkaban (Harr... | 435 | eng | 4.57 | 2946694 | 58023 | J.K. Rowling | 1999-07-08 | 2004-05-01 | Mass Market Paperback | 45175 | Harry Potter | 3 |
| 4 | Harry Potter and the Goblet of Fire (Harry Pot... | 734 | eng | 4.56 | 2705676 | 48637 | J.K. Rowling | 2000-07-08 | 2002-09-28 | Paperback | 45175 | Harry Potter | 4 |
books.describe()
| average_rating | ratings_count | text_reviews_count | |
|---|---|---|---|
| count | 7.027431e+06 | 7.027431e+06 | 7.027431e+06 |
| mean | 3.306188e+00 | 1.945861e+04 | 6.417258e+02 |
| std | 1.435734e+00 | 1.609008e+05 | 4.169806e+03 |
| min | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 |
| 25% | 3.360000e+00 | 3.000000e+00 | 0.000000e+00 |
| 50% | 3.810000e+00 | 4.500000e+01 | 5.000000e+00 |
| 75% | 4.080000e+00 | 7.710000e+02 | 6.400000e+01 |
| max | 5.000000e+00 | 7.400639e+06 | 1.745240e+05 |
Data Cleaning on books:
books2 = books
books2.dropna(subset=["title", "num_pages", "language", "average_rating", "ratings_count", "author_name", "original_publication_date", "publication_date","text_reviews_count","format","series_id","series_name","series_position"], inplace=True)
books2.shape[0]
7027431
min(books2['title'])
''
I can see blank Title in the books dataset, I will discard such rows and apply the same technique to other columns.
books2= books2[books2.apply(lambda x: x.title!='' and x.author_name!='', axis=1)]
books2.shape[0]
7027398
# Filter out rows with incorrect values in "num_pages" (e.g., non-numeric values)
books2['num_pages'] = pd.to_numeric(books2['num_pages'], errors='coerce')
books2 = books2[books2['num_pages'].notna()]
books2 = books2[books2['num_pages'] != 0]
min_num_pages = books2["num_pages"].min()
<ipython-input-19-337f7037a939>:2: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy books2['num_pages'] = pd.to_numeric(books2['num_pages'], errors='coerce')
books2 = books2[(books2[["average_rating", "ratings_count", "num_pages","text_reviews_count"]] >= 0).all(axis=1)]
from datetime import datetime
books2["original_publication_date"] = pd.to_datetime(books2["original_publication_date"], errors='coerce')
books2["original_publication_date"] = pd.to_datetime(books2["original_publication_date"])
present_date = datetime.now()
books2 = books2[books2['original_publication_date'] <= present_date]
books2["original_publication_date"].max()
Timestamp('2023-10-14 00:00:00')
books2 = books2[books2["author_name"] != "NOT A BOOK"]
books2 = books2[books2["language"] != ""]
books2 = books2.drop_duplicates(subset = ["title"])
books2.shape[0]
1271100
Exploratory Data Analysis on Authors set:
media = authors3['average_rating'].mean()
mediana = authors3['average_rating'].median()
minimo = authors3['average_rating'].min()
massimo = authors3['average_rating'].max()
print("Base statistics on average_rating")
print("mean", round(media, 2))
print("median", mediana)
print("min and max", minimo, massimo)
plt.boxplot(authors2["average_rating"], showfliers=True, patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2})
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of average_rating")
plt.show
Base statistics on average_rating mean 3.71 median 3.95 min and max 0.0 5.0
<function matplotlib.pyplot.show(close=None, block=None)>
media = authors3['fans_count'].mean()
mediana = authors3['fans_count'].median()
minimo = authors3['fans_count'].min()
massimo = authors3['fans_count'].max()
print("Base statistics on fans_count")
print("mean", round(media, 2))
print("median", mediana)
print("min and max", minimo, massimo)
plt.boxplot(authors2["fans_count"], patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2}, showfliers=True)
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of fans_count")
plt.show
Base statistics on fans_count mean 127.33 median 5.0 min and max 0 455358
<function matplotlib.pyplot.show(close=None, block=None)>
media = authors3['ratings_count'].mean()
mediana = authors3['ratings_count'].median()
minimo = authors3['ratings_count'].min()
massimo = authors3['ratings_count'].max()
print("Base statistics on ratings_count")
print("mean", round(media, 2))
print("median", mediana)
print("min and max", minimo, massimo)
plt.boxplot(authors2["ratings_count"], patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2}, showfliers=True)
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of fans_count")
plt.show
Base statistics on ratings_count mean 5474.95 median 51.0 min and max 0 27003752
<function matplotlib.pyplot.show(close=None, block=None)>
conteggio_output = authors3['gender'].value_counts().reset_index()
conteggio_output.columns = ['gender', 'count']
conteggio_output_ordinato = conteggio_output.sort_values(by='count', ascending=False)
conteggio_output_ordinato = conteggio_output_ordinato[conteggio_output_ordinato["gender"] != ""]
maschifemmine = conteggio_output_ordinato[conteggio_output_ordinato["gender"].isin(["male", "female"])]
riga_altro = pd.DataFrame({"gender": ["other"], "count": [conteggio_output_ordinato["count"].sum() - maschifemmine["count"].sum()]})
maschifemmine = pd.concat([maschifemmine, riga_altro], ignore_index=True)
plt.figure(figsize=(6, 6))
plt.pie(maschifemmine['count'], labels=maschifemmine['gender'], autopct='%1.1f%%', colors=['lightblue', 'lightgreen', 'lightcoral'], startangle=140)
plt.title('')
plt.axis('equal')
plt.show()
Exploratory Data Analysis on Books Set
media = books2['num_pages'].mean()
mediana = books2['num_pages'].median()
minimo = books2['num_pages'].min()
massimo = books2['num_pages'].max()
print("Base statistics on num_pages")
print("mean", round(media, 1))
print("median", mediana)
print("min and max", minimo, massimo)
plt.boxplot(books2["num_pages"], patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2}, showfliers=True)
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of num_pages")
plt.show
Base statistics on num_pages mean 3649.7 median 239.0 min and max 1.0 2147483647.0
<function matplotlib.pyplot.show(close=None, block=None)>
media = books2['average_rating'].mean()
mediana = books2['average_rating'].median()
minimo = books2['average_rating'].min()
massimo = books2['average_rating'].max()
print("Base statistics on average_rating")
print("mean", round(media, 2))
print("median", round(mediana, 2))
print("min and max", minimo, massimo)
plt.boxplot(books2["average_rating"], patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2}, showfliers=True)
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of average_rating")
plt.show
Base statistics on average_rating mean 3.7 median 3.88 min and max 0.0 5.0
<function matplotlib.pyplot.show(close=None, block=None)>
media = books2['ratings_count'].mean()
mediana = books2['ratings_count'].median()
minimo = books2['ratings_count'].min()
massimo = books2['ratings_count'].max()
print("Base statistics on ratings_count")
print("mean", round(media, 2))
print("median", round(mediana, 2))
print("min and max", minimo, massimo)
plt.boxplot(books2["ratings_count"], patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2}, showfliers=True)
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of ratings_count")
plt.show
Base statistics on ratings_count mean 19652.52 median 117.0 min and max 0 7400639
<function matplotlib.pyplot.show(close=None, block=None)>
books2["original_publication_date"] = pd.to_datetime(books2["original_publication_date"], errors='coerce')
books2["original_publication_date"] = pd.to_datetime(books2["original_publication_date"])
# Trova la data minima
data_minima = books2["original_publication_date"].min()
# Trova la data massima
data_massima = books2["original_publication_date"].max()
# Stampa i risultati
print("Minimum Date:", data_minima)
print("Maximum Date:", data_massima)
Minimum Date: 1678-01-01 00:00:00 Maximum Date: 2023-10-14 00:00:00
conteggio_output = books2['language'].value_counts().reset_index()
conteggio_output.columns = ['language', 'count']
conteggio_output = conteggio_output.dropna() # Rimuovo le righe con valori mancanti
conteggio_output_ordinato = conteggio_output.sort_values(by='count', ascending=False)
print(conteggio_output_ordinato.head(10))
primi10 = conteggio_output_ordinato.head(10)
plt.bar(primi10["language"], primi10['count'])
plt.xlabel('Languages')
plt.ylabel('Count')
plt.show()
language count 0 eng 520345 1 spa 69574 2 ger 69184 3 ita 66776 4 fre 61948 5 por 49079 6 en-US 41403 7 nl 39031 8 ara 30207 9 en-GB 28752
del authors
del books
author_book_counts = books2.groupby('author_name')['title'].count().reset_index()
author_book_counts = author_book_counts.sort_values(by='title', ascending=False)
# author names and book counts for top 50 authors
plt.figure(figsize=(12, 6))
plt.bar(author_book_counts[:50]['author_name'], author_book_counts[:50]['title'])
plt.xticks(rotation=90)
plt.xlabel('Author Name')
plt.ylabel('Number of Books')
plt.title('Number of Books for Top 50 Authors')
plt.show()
books2_sorted = books2.sort_values(by='text_reviews_count', ascending=False)
print(f"The book with the highest number of text reviews is '{books2_sorted['title'][1]}' with {books2_sorted['text_reviews_count'][1]} reviews.")
The book with the highest number of text reviews is 'Harry Potter and the Sorcerer's Stone (Harry Potter, #1)' with 116930 reviews.
# Sort books by average rating in descending order for the top ten
best_books = books2.sort_values(by='average_rating', ascending=False)
ten_best_books= best_books.head(10)[['title','average_rating']]
# Sort books by average rating in ascending order for the ten worst
worst_books = books2.sort_values(by='average_rating', ascending=True)
ten_worst_books= worst_books.head(10)[['title','average_rating']]
# Print the top ten and ten worst books
print("Top Ten Books with Highest Average Rating:\n")
print(ten_best_books)
print("\nTen Worst Books with Lowest Average Rating:\n")
print(ten_worst_books)
Top Ten Books with Highest Average Rating:
title average_rating
3355748 The Gospel of Matthew/The Death of Ivan Ilych/... 5.0
4684994 Gigia ha il Diabete 5.0
6256490 Now Is Not The Time For Trumpets 5.0
4685312 Whiz Tanner and the Vanishing Diamond (Tanner-... 5.0
4685142 My Favourite Children's Songs 5.0
4685124 The World Is a Scary Place 5.0
3472547 Soulis Joe's Lost Mine 5.0
3472552 Dissecting Sean Connor 5.0
3472556 A Spoonful of Sugar 5.0
3472582 Бог в Ню Йорк 5.0
Ten Worst Books with Lowest Average Rating:
title average_rating
4414879 Lionne; Or the Doom of Deville 0.0
3100783 Cómo conocer los instrumentos de orquesta 0.0
2238885 The Changing Face Of Warminster 0.0
844390 Spectacular Wineries of Napa Valley: A Captiva... 0.0
5540582 Risk Management: Gestão, Relato e Auditoria do... 0.0
4697326 Wagner's Heroes 0.0
844237 La conspiración. El golpe de estado difuso 0.0
4697334 Segovia. Pueblo, ciudad y tierra. Horizonte hi... 0.0
3100920 De la connaissance de soi-même 0.0
6799524 Youth Worship and Sing 0.0
lang_counts = books2['language'].value_counts().reset_index()
lang_counts.columns = ['language', 'count'] # Correggi l'assegnazione delle colonne
(lang_counts.shape[0])
top50lang = lang_counts.head(50)
(top50lang.head(2))
top10lang = lang_counts[lang_counts["language"].isin(["eng", "ger", "spa", "fre", "ita", "en-US", "por", "en-GB", "nl", "ara"])]
(top10lang.head(10))
riga_altro = pd.DataFrame({"language": ["other 244 languages"], "count": [lang_counts["count"].sum() - top10lang["count"].sum()]})
top10lang = pd.concat([top10lang, riga_altro], ignore_index=True)
plt.figure(figsize=(8, 8)) # Imposta le dimensioni del grafico
plt.pie(top10lang['count'], labels=top10lang['language'], autopct='%1.1f%%', colors=['blue', 'green', 'red', 'yellow', 'orange', 'purple', 'pink', 'lightblue', 'brown', 'gray', 'cyan'], startangle=140)
plt.title('')
plt.axis('equal')
plt.show()
plt.hist(lang_counts['count'], bins=50, edgecolor='k')
plt.xlabel('Number of books')
plt.ylabel('Number of languages')
plt.title('Distribution of number of books per languages')
plt.show()
books250more = books2[(books2[["num_pages"]] > 250).all(axis=1)]
print(f'Number of books with more than 250 pages is {books250more.shape[0]}')
Number of books with more than 250 pages is 597073
top50author = author_book_counts.head(50)
top50author = top50author.rename(columns={"author_name": "name"})
merged_df = pd.merge(top50author, authors3, on='name', how='left')
merged_df[["name","fans_count"]].head(5)
| name | fans_count | |
|---|---|---|
| 0 | Various | NaN |
| 1 | Agatha Christie | NaN |
| 2 | Anonymous | NaN |
| 3 | Walt Disney Company | NaN |
| 4 | Enid Blyton | NaN |
Appearance of NaN values. So I will drop them.
merged_df.dropna(subset=['fans_count'],inplace=True)
merged_df[["name","fans_count"]].head(5)
| name | fans_count | |
|---|---|---|
| 5 | Nora Roberts | 41402.0 |
| 13 | Terry Pratchett | 35674.0 |
| 15 | J.R.R. Tolkien | 59406.0 |
| 19 | Rumiko Takahashi | 1395.0 |
| 20 | CLAMP | 2630.0 |
# Plot the distribution of fans count
plt.figure(figsize=(8, 4))
plt.hist(merged_df['fans_count'], bins=50, edgecolor='k')
plt.xlabel('Fans Count')
plt.ylabel('Number of Authors')
plt.title('Distribution of Fans Count for the 50 Most Prolific Authors')
plt.show()
plt.figure(figsize=(8, 3))
plt.bar(merged_df['name'], merged_df['fans_count']/30000) #i have normalized the count
plt.xticks(rotation=90)
plt.xlabel('Author Name')
plt.ylabel('Fans Count')
plt.title('Fans Count for Top 50 Prolific Authors')
plt.show()
plt.figure(figsize=(6, 3))
plt.boxplot(merged_df['fans_count'], vert=False)
plt.xlabel('Fans Count')
plt.title('Distribution of Fans Count for the 50 Most Prolific Authors (Box Plot)')
plt.show()
data sets loaded and cleaned previously as: authors3, books2
books2["original_publication_date"].min()
Timestamp('1678-01-01 00:00:00')
books2["original_publication_date"].max()
Timestamp('2023-10-14 00:00:00')
The number of books published that year.
The total number of pages written that year.
The most prolific month of that year.
The longest book written that year.
def books_info_for_year(year):
books_in_year = books2[books2['original_publication_date'].dt.year == year]
# total number of books published in the given year
Num_Books = len(books_in_year)
# total number of pages written in the given year
Total_Pages = books_in_year.loc[:,'num_pages'].sum()
# to count the most prolific month
#books_in_year['publication_month'] = books_in_year['original_publication_date'].dt.month
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
Most_Prolific_Month = None
longest_book = None
if not books_in_year.empty:
# to find the most prolific month
#books_in_year['month'] = books_in_year['original_publication_date'].dt.month
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
Most_Prolific_Month = books_in_year['month'].value_counts().idxmax()
# the longest book written in that year
longest_book = books_in_year[books_in_year['num_pages'] == books_in_year['num_pages'].max()]['title'].values[0]
return Num_Books, Total_Pages, Most_Prolific_Month, longest_book
import time
year = 2003
start_time=time.time()
result = books_info_for_year(year)
end_time=time.time()
print(result)
print(f"Time taken: {end_time - start_time:.2f} seconds")
(27855, 7902848.0, 1, 'Soldadura, Nivel Duo Guía del estudiante') Time taken: 0.09 seconds
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month <ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
years = books2['original_publication_date'].dt.year.unique()
yearly_info = pd.DataFrame(columns=['Year', 'Num_Books', 'Total_Pages', 'Most_Prolific_Month', 'Longest_Book'])
start_time=time.time()
for year in years:
Num_Books, Total_Pages, Most_Prolific_Month, Longest_Book = books_info_for_year(year)
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
end_time=time.time()
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
Time taken to load DF: 22.99 seconds
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
print(f"Time taken to load DF: {end_time - start_time:.2f} seconds")
Time taken to load DF: 22.99 seconds
print(yearly_info.head(10))
Year Num_Books Total_Pages Most_Prolific_Month \
0 2003 27855 7902848.0 1
1 1997 19107 5390938.0 1
2 1998 20258 5701355.0 1
3 1999 21630 6094817.0 1
4 2000 24520 7166551.0 1
5 2005 33261 9590228.0 1
6 1979 7191 1944814.0 1
7 1996 18071 5091901.0 1
8 2002 25920 7381552.0 1
9 1984 9296 2552604.0 1
Longest_Book
0 Soldadura, Nivel Duo Guía del estudiante
1 مجموعة الفتاوى
2 Goethes Poetische Werke: Vollständige Ausgabe
3 ميخائيل نعيمه المجموعة الكاملة
4 Combo - As Crônicas de Gelo e Fogo
5 幽・遊・白書 完全版 全15巻・全巻セット (幽・遊・白書 完全版 YuYu Hakusho...
6 Gordana kraljica Hrvata (1-12)
7 The Persian Encyclopedia (دايرة المعارف فارسى)
8 The Works of John Brown of Wamphray (7 Volumes...
9 تفسير التحرير والتنوير
print(yearly_info.tail(10))
Year Num_Books Total_Pages Most_Prolific_Month \
336 1738 3 254.0 1
337 1705 10 7538.0 1
338 1694 6 571.0 1
339 1711 11 4129.0 1
340 2021 18 7544.0 1
341 1701 2 83.0 1
342 1700 4 1202.0 1
343 2022 7 1600.0 12
344 1679 3 990.0 1
345 2023 2 412.0 5
Longest_Book
336 De la conversation: Suivi d’un essai de Jonath...
337 روح البيان في تفسير القرآن
338 Cuentos de antaño
339 Voyages de Monsieur le chevalier Chardin en Pe...
340 The Navigator's Children (The Last King of Ost...
341 Tabiat Işığı ile Hakikati Arama
342 Mémoires de M. D'Artagnan, Tome 1
343 Annabel Horton: Lost Witch of Salem
344 Strange Stories from a Chinese Studio, Vol. 1 ...
345 Short & Happy [or Not]
# Following implementation is done by Chat GPT 4.0:
def books_info(year):
# filter the dataframe by the given year
books_in_year = books2[books2['original_publication_date'].dt.year == year]
# calculate the number of books published that year
num_books = books_in_year.shape[0]
# calculate the total number of pages written that year
total_pages = books_in_year['num_pages'].sum()
# calculate the most prolific month of that year
most_prolific_month = books_in_year['original_publication_date'].dt.month.value_counts().idxmax()
# find the longest book written that year
longest_book = books_in_year.loc[books_in_year['num_pages'].idxmax()]['title']
return {
"Number of books published": num_books,
"Total number of pages": total_pages,
"Most prolific month": most_prolific_month,
"Longest book": longest_book,
}
print(books_info(2003))
{'Number of books published': 27855, 'Total number of pages': 7902848.0, 'Most prolific month': 1, 'Longest book': 'Soldadura, Nivel Duo Guía del estudiante'}
# Following function is implemented by Bard LLM of Google:
import pandas as pd
def get_book_stats_by_year(books2, year):
"""Get book stats by year.
Args:
books2: A pandas DataFrame containing book data.
year: The year to get book stats for.
Returns:
A dictionary containing the following information:
* The number of books published that year.
* The total number of pages written that year.
* The most prolific month of that year.
* The longest book written that year.
"""
# Filter the books2 DataFrame to only include books published in the given year.
books_by_year = books2[books2['original_publication_date'].dt.year == year]
# Get the number of books published that year.
num_books_published = len(books_by_year)
# Get the total number of pages written that year.
total_pages_written = books_by_year['num_pages'].sum()
# Get the most prolific month of that year.
most_prolific_month = books_by_year['original_publication_date'].dt.month.value_counts().nlargest(1).index[0]
# Get the longest book written that year.
longest_book = books_by_year[books_by_year['num_pages'] == books_by_year['num_pages'].max()]
return {
'num_books_published': num_books_published,
'total_pages_written': total_pages_written,
'most_prolific_month': most_prolific_month,
'longest_book': longest_book
}
get_book_stats_by_year(books2, 2003)
{'num_books_published': 27855,
'total_pages_written': 7902848.0,
'most_prolific_month': 1,
'longest_book': title num_pages language \
4026121 Soldadura, Nivel Duo Guía del estudiante 9998.0 spa
average_rating ratings_count text_reviews_count author_name \
4026121 4.5 2 0 NCCER
original_publication_date publication_date
4026121 2003-08-08 2012-11-01 }
Analyis and Remarks on the LLM Implementation:
< write an essay here >
eponymous_authors = authors3[authors3.duplicated('name', keep=False)]
if not eponymous_authors.empty:
print("Eponymous authors found: "+str(eponymous_authors.shape[0]))
print(eponymous_authors['name'])
Eponymous authors found: 18 8639 Peter Marshall 14943 Christopher Phillips 19037 William Messner-Loebs 74780 Peter Marshall 99922 Yordan Yovkov 134763 محمد نجيب 165580 Jackson Butch Guice 171064 محمد نجيب 178267 Q. Hayashida 185467 Dimitar Dimov 193531 Jackson Butch Guice 194321 Q. Hayashida 200003 Christopher Phillips 228145 Yordan Yovkov 270233 James C.L. Carson 311093 William Messner-Loebs 314855 Dimitar Dimov 315853 James C.L. Carson Name: name, dtype: object
def get_author_books_v0(author_ids):
author_books = {}
for author_id in author_ids:
matching_rows = authors3[authors3['id'] == author_id]
if not matching_rows.empty:
author_name = matching_rows.iloc[0]['name']
# Check if 'author_name' is present in the 'books2' DataFrame
if 'author_name' in books2.columns:
books = books2[books2['author_name'] == author_name]['title'].tolist()
author_books[author_name] = books
else:
# Handle the case where 'author_name' column is not found
author_books[author_name] = ["Author's Books Not Found"]
else:
# Handle the case where no matching author is found
author_books[author_name] = ["Author Not Found"]
return author_books
Top 20 authors by average rating
top_20_authors_v0 = authors3.nlargest(20, 'average_rating')
top_20_author_ids_v0 = top_20_authors_v0['id'].tolist()
Get books of the top 20 authors
top_20_author_books_v0 = get_author_books_v0(top_20_author_ids_v0)
longest_title_v0 = max(max(top_20_author_books_v0.values(), key=len), key=len)
overall_longest_title_v0 = max(books2['title'], key=len)
shortest_title_v0 = min(books2['title'], key=len)
print("Top 20 authors' books:")
for author, books in top_20_author_books_v0.items():
print(f"{author}: {books}")
Top 20 authors' books: James T. Holmes: [] Jessie (Pierce) Trebesch: [] Staci Mauney: [] Robert Sidney: ['The Poems of Robert Sidney'] Christine K. Fields: [] Ondeane Lourens: [] Bonnie Kelso: [] Nikos Dimitriou: [] J.M. van Zuiden: [] Archimandrite Gabriel: [] Carlo de Incontrera: [] Lavelle Carlson: [] Tiffany Post: [] Robert Reed: [] Catherine Soto: [] Nancy Harding: [] Alex Johnson: [] Xavier Seoane Rivas: ['A dama da noite'] Fran Moeller Gatins: [] Mark D. Swartz: []
print(f"Longest book title among the top 20 authors: {longest_title_v0}")
Longest book title among the top 20 authors: The Poems of Robert Sidney
if longest_title_v0 == overall_longest_title_v0:
print("The longest book title among the top 20 authors is the same as the longest book title overall.")
else:
print("The longest book title among the top 20 authors is not the same as the longest book title overall.")
The longest book title among the top 20 authors is not the same as the longest book title overall.
print(f"Overall Longest book title is: {overall_longest_title_v0}")
Overall Longest book title is: Lecture on Human Happiness: Being the First of a Series of Lectures on That Subject in Which Will Be Comprehended a General Review of the Causes of the Existing Evils of Society [And a Development of Means by Which They May Be Permanently and Effectual...
print(f"Shortest book title overall: {shortest_title_v0}")
Shortest book title overall: Q
# Identify author IDs with no books in the books DataFrame
authors_with_books = books2['author_name'].unique()
authors_with_books
array(['J.K. Rowling', 'Douglas Adams', 'Bill Bryson', ..., 'A.C. Spahn',
'Alexis Koetting', 'Chad A. Clark'], dtype=object)
authors_clean = authors3[authors3['name'].isin(authors_with_books)]
authors_clean.shape[0]
138645
def get_author_books(author_ids):
author_books = {}
for author_id in author_ids:
matching_rows = authors_clean[authors_clean['id'] == author_id]
if not matching_rows.empty:
author_name = matching_rows.iloc[0]['name']
# Check if 'author_id' is present in the 'books2' DataFrame
if 'author_name' in books2.columns:
books = books2[books2['author_name'] == author_name]['title'].tolist()
author_books[author_name] = books
else:
# Handle the case where 'author_id' column is not found
author_books[author_name] = ["Author's Books Not Found"]
else:
# Handle the case where no matching author is found
author_books[author_name] = ["Author Not Found"]
return author_books
top_20_authors = authors_clean.nlargest(20, 'average_rating')
top_20_author_ids = top_20_authors['id'].tolist()
top_20_author_books = get_author_books(top_20_author_ids)
longest_title = max(max(top_20_author_books.values(), key=len), key=len)
overall_longest_title = max(books2['title'], key=len)
shortest_title = min(books2['title'], key=len)
print("Top 20 authors' books:")
for author, books in top_20_author_books.items():
print(f"{author}: {books}")
Top 20 authors' books: Robert Sidney: ['The Poems of Robert Sidney'] Xavier Seoane Rivas: ['A dama da noite'] Lori Walters: ['The Day that Rocked the 4th Dimension'] Sean McSweeney: ['The On-And-On Tin'] Robert Jahn: ['Der salzige Fluss'] E.E.E.: ['A Warm Mirror Neuron On A Memory'] Darryl Scriven: ['The Love Commitment'] Julian Weiss: ['The Mester de Clerecía: Intellectuals and Ideologies in Thirteenth Century Castile', 'Locating the Middle Ages: The Spaces and Places of Medieval Culture'] John F. Wilson: ['Obra Morava en Nicaragua: trasfondo y breve historia'] Becky Long: ['Transition Nutrition: The Easy, Sustainable Way to Change Your Diet AND the Reasons Why You Should Change Now (Volume 1)'] Thaddeus Stevens: ['The Papers Of Thaddeus Stevens Volume 1: January 1814-March 1865'] Donald W. Bartow: ['The Gospel According to Mary, Mother of Jesus'] Peter W. Smorynski: ['A Shadow of Chaos (Universal War: ARM X, #2)'] Rodrigo Duarte Casar: ['Antónimos Anónimos: una Recopilación de Usos Creativos del Lenguaje, Frecuentemente Involuntarios'] Greg Long: ['The New Game Changers: Driving Performance by Focusing on What Matters'] Thaddeus W.H. Leavitt: ['History of Leeds and Grenville, Ontario, from 1749-1879 with Illustrations and Biographical Sketches of Some of its Prominent Men and Pioneers'] George Smith: ["Smith's Introduction to Industrial Mycology"] Antonio Rumeu de Armas: ['Alfonso De Ulloa, Introductor de la Cultura Española en Italia', 'En Colom a Barcelona'] Mrs. John King Van Rensselaer: ['Newport, Our Social Capital'] Alan J. Rocke: ['Image and Reality: Kekulé, Kopp, and the Scientific Imagination']
print(f"Longest book title among the top 20 authors: {longest_title}")
Longest book title among the top 20 authors: The Mester de Clerecía: Intellectuals and Ideologies in Thirteenth Century Castile
if longest_title == overall_longest_title:
print("The longest book title among the top 20 authors is the same as the longest book title overall.")
else:
print("The longest book title among the top 20 authors is not the same as the longest book title overall.")
The longest book title among the top 20 authors is not the same as the longest book title overall.
print(f"Overall Longest book title is: {overall_longest_title}")
Overall Longest book title is: Lecture on Human Happiness: Being the First of a Series of Lectures on That Subject in Which Will Be Comprehended a General Review of the Causes of the Existing Evils of Society [And a Development of Means by Which They May Be Permanently and Effectual...
print(f"Shortest book title overall: {shortest_title}")
Shortest book title overall: Q
top10fansbasis= authors_clean.nlargest(10,'fans_count')
plt.figure(figsize=(8, 3))
plt.barh(top10fansbasis['name'], top10fansbasis['fans_count'])
plt.xlabel('Number of Fans')
plt.ylabel('Author Name')
plt.title('Top 10 Most Influential Authors on the basis of Fans count')
plt.gca().invert_yaxis() # Inverting the y-axis to display the most influential at the top
plt.show()
top10worksbasis=authors_clean.nlargest(10,'works_count')
plt.figure(figsize=(8, 3))
plt.barh(top10worksbasis['name'], top10worksbasis['works_count'])
plt.xlabel('Number of Books')
plt.ylabel('Author Name')
plt.title('Top 10 Most Influential Authors on the basis of Number of Books')
plt.gca().invert_yaxis() # Inverting the y-axis to display the most influential at the top
plt.show()
Now I will combine the two columns to find the overall influence based on the combined metrics.
authors_clean['influence'] = authors_clean['fans_count'] * authors_clean['works_count']
<ipython-input-77-214fb8cd2b99>:1: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy authors_clean['influence'] = authors_clean['fans_count'] * authors_clean['works_count']
top10authors=authors_clean.nlargest(10,'influence')
plt.figure(figsize=(8, 3))
plt.barh(top10authors['name'], top10authors['influence'])
plt.xlabel('Combined Influence Metric')
plt.ylabel('Author Name')
plt.title('Top 10 Most Influential Authors based on Fans Count and Books Count')
plt.gca().invert_yaxis() # Inverting the y-axis to display the most influential at the top
plt.show()
Hence, the Most Influential Author is James Patterson.
influential_author_names = top10authors['name'].tolist()
print(influential_author_names)
['James Patterson', 'George R.R. Martin', 'Rick Riordan', 'J.K. Rowling', 'Cassandra Clare', 'Brandon Sanderson', 'Nora Roberts', 'Haruki Murakami', 'Diana Gabaldon', 'Nicholas Sparks']
I am filtering the dataset only on the basis of the top 10 influential author names:
book_series_data = books2[books2['author_name'].isin(influential_author_names)]
book_series_data.shape[0]
7469
book_series_data.head(3)
| title | num_pages | language | average_rating | ratings_count | text_reviews_count | author_name | original_publication_date | publication_date | format | series_id | series_name | series_position | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Harry Potter and the Order of the Phoenix (Har... | 870.0 | eng | 4.50 | 2628006 | 44716 | J.K. Rowling | 2003-06-21 | 2004-09 | Paperback | 45175 | Harry Potter | 5 |
| 1 | Harry Potter and the Sorcerer's Stone (Harry P... | 309.0 | eng | 4.48 | 7377351 | 116930 | J.K. Rowling | 1997-06-26 | 2003-11-01 | Hardcover | 45175 | Harry Potter | 1 |
| 2 | Harry Potter and the Chamber of Secrets (Harry... | 352.0 | eng | 4.43 | 2855044 | 55286 | J.K. Rowling | 1998-07-02 | 2003-11-01 | Hardcover | 45175 | Harry Potter | 2 |
series = book_series_data.groupby('author_name')['series_name'].unique()
series
author_name Brandon Sanderson [Elantris, Mistborn, Alcatraz Versus The Evil ... Cassandra Clare [The Mortal Instruments, The Infernal Devices,... Diana Gabaldon [Outlander, The Outlandish Companions, Lord Jo... George R.R. Martin [A Song of Ice and Fire, , Wild Cards, The Art... Haruki Murakami [海辺のカフカ, , ノルウェイの森, ねじまき鳥クロニクル, The Rat, ねじまき鳥... J.K. Rowling [Harry Potter, , Hogwarts Library, Harry Potte... James Patterson [, Alex Cross, Women's Murder Club, Maximum Ri... Nicholas Sparks [, Jeremy Marsh & Lexie Darnell, The Notebook] Nora Roberts [, Gallaghers of Ardmore, Circle Trilogy, The ... Rick Riordan [Percy Jackson and the Olympians, Tres Navarre... Name: series_name, dtype: object
longest_name = series.apply(lambda x: max(x, key=len))
longest_name
author_name Brandon Sanderson Alcatraz Versus The Evil Librarians Cassandra Clare The Mortal Instruments: Graphic Novel Diana Gabaldon Outlander Split-Volume Edition George R.R. Martin Game of Thrones / Das Lied von Eis und Feuer (... Haruki Murakami ねじまき鳥クロニクル #3 J.K. Rowling Harry Potter Persian/Farsi Split-Volume Edition James Patterson The Best American Mystery Stories Nicholas Sparks Jeremy Marsh & Lexie Darnell Nora Roberts Time and Again: Hornblower-Stone Rick Riordan Percy Jackson and the Olympians: The Graphic N... Name: series_name, dtype: object
longest_series_name = longest_name[longest_name.str.len().idxmax()]
author_with_longest_series=", ".join(book_series_data[book_series_data['series_name']==longest_series_name]['author_name'].unique())
print("Author with the Longest Series Name:", author_with_longest_series)
print("Longest Series Name:", longest_series_name)
Author with the Longest Series Name: George R.R. Martin Longest Series Name: Game of Thrones / Das Lied von Eis und Feuer (Audible)
unique_formats = book_series_data.groupby('author_name')['format'].unique()
unique_formats
author_name Brandon Sanderson [Mass Market Paperback, Hardcover, ebook, Pape... Cassandra Clare [Hardcover, Paperback, Broché, , Mass Market P... Diana Gabaldon [Paperback, Mass Market Paperback, Hardcover, ... George R.R. Martin [Paperback, Mass Market Paperback, Hardcover, ... Haruki Murakami [Paperback, Hardcover, , Taschenbuch, 単行本, Mas... J.K. Rowling [Paperback, Hardcover, Mass Market Paperback, ... James Patterson [Paperback, Mass Market Paperback, Hardcover, ... Nicholas Sparks [Paperback, Hardcover, Mass Market Paperback, ... Nora Roberts [Mass Market Paperback, Paperback, , Hardcover... Rick Riordan [Hardcover, Paperback, Audio CD, Board Book, ,... Name: format, dtype: object
formats_count = unique_formats.apply(lambda x: len(x))
formats_count
author_name Brandon Sanderson 12 Cassandra Clare 12 Diana Gabaldon 11 George R.R. Martin 21 Haruki Murakami 18 J.K. Rowling 15 James Patterson 14 Nicholas Sparks 10 Nora Roberts 27 Rick Riordan 10 Name: format, dtype: int64
import matplotlib.pyplot as plt
plt.figure(figsize=(8, 6))
formats_count.plot(kind='bar')
plt.title('Distribution of Formats for Top 10 Authors')
plt.xlabel('Author Name')
plt.ylabel('Number of Unique Formats')
plt.show()
summary_by_gender = top10authors.groupby('gender')[['fans_count', 'average_rating', 'text_reviews_count']].agg(['mean', 'std', 'min', 'max'])
summary_by_gender
| fans_count | average_rating | text_reviews_count | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| mean | std | min | max | mean | std | min | max | mean | std | min | max | |
| gender | ||||||||||||
| female | 164740.500000 | 87582.167841 | 41402 | 238560 | 4.265000 | 0.151987 | 4.09 | 4.46 | 328483.750000 | 225395.936540 | 127360 | 606373 |
| male | 201767.333333 | 107979.658858 | 86123 | 339346 | 4.181667 | 0.197019 | 3.96 | 4.38 | 249589.833333 | 78958.792016 | 167603 | 354145 |
Summary:
The table provides insights into the top 10 authors, specifically in terms of 'fans_count,' 'average_rating,' and 'text_reviews_count,' divided by gender (female and male). Here's a summary of the key statistics for each gender:
Female Authors:
The mean 'fans_count' for female authors is approximately 164,740.5, with a standard deviation of 87,582.17. The minimum 'fans_count' is 41,402, and the maximum is 238,560. The mean 'average_rating' for female authors is around 4.265, with a standard deviation of 0.152. The lowest average rating is 4.09, and the highest is 4.46. The mean 'text_reviews_count' for female authors is approximately 328,483.75, with a standard deviation of 225,395.94. The lowest text reviews count is 127,360, and the highest is 606,373.
Male Authors:
The mean 'fans_count' for male authors is about 201,767.33, with a standard deviation of 107,979.66. The minimum 'fans_count' is 86,123, and the maximum is 339,346. The mean 'average_rating' for male authors is approximately 4.182, with a standard deviation of 0.197. The lowest average rating is 3.96, and the highest is 4.38. The mean 'text_reviews_count' for male authors is around 249,589.83, with a standard deviation of 78,958.79. The lowest text reviews count is 167,603, and the highest is 354,145.
I asked ChatGPT to implement a Visualisation for this summary statistics and here it goes:
import seaborn as sns
# Sample data (replace with your actual data)
mean_data = {
'gender': ['female', 'male'],
'fans_count_mean': [164740.5, 201767.33],
'average_rating_mean': [4.265, 4.182],
'text_reviews_count_mean': [328483.75, 249589.83]
}
# Create a DataFrame from the sample data
mean_df = pd.DataFrame(mean_data)
# Set the style for Seaborn
sns.set(style="whitegrid")
# Create a figure with subplots
fig, axes = plt.subplots(1, 3, figsize=(15, 5))
# Bar chart for mean fans_count
sns.barplot(x="gender", y="fans_count_mean", data=mean_df, ax=axes[0])
axes[0].set(title="Mean Fans Count")
# Bar chart for mean average_rating
sns.barplot(x="gender", y="average_rating_mean", data=mean_df, ax=axes[1])
axes[1].set(title="Mean Average Rating")
# Bar chart for mean text_reviews_count
sns.barplot(x="gender", y="text_reviews_count_mean", data=mean_df, ax=axes[2])
axes[2].set(title="Mean Text Reviews Count")
# Add a common title for the subplots
plt.suptitle("Summary Statistics by Gender")
# Show the plots
plt.show()
# Create box plots to visualize data spread (you can adapt this)
# Example for 'fans_count'
plt.figure(figsize=(8, 3))
sns.boxplot(x='gender', y='fans_count', data=top10authors)
plt.title("Box Plot of Fans Count by Gender")
plt.show()
Conclusions
Fans Count:
Male authors, on average, have a slightly higher number of fans compared to female authors. However, there is significant variability within both groups, as indicated by the standard deviations. The minimum and maximum fans count for both male and female authors is substantial, indicating a wide range of popularity among the top 10 authors.
Average Rating:
Female authors, on average, have a slightly higher average rating compared to male authors. Both groups have relatively high average ratings. The standard deviations for average rating are relatively low, suggesting that most top 10 authors in both groups receive consistently high ratings.
Text Reviews Count:
Female authors have a notably higher mean text reviews count compared to male authors. This indicates that books by female authors in the top 10 receive more text reviews, on average. The standard deviations for text reviews count are high, indicating variability in the number of reviews received by authors in both groups. Overall, it's essential to note that these conclusions are based on the top 10 authors in the dataset and may not be representative of all authors.
Both male and female authors in the top 10 are popular, with a significant number of fans. Female authors, on average, tend to have slightly higher average ratings and receive more text reviews. There is variability in the popularity, average ratings, and reviews count within both groups. However, it's important to consider that these insights are specific to the top 10 authors in the dataset and should not be generalized to all authors. Additional factors, such as the specific books or genres written by these authors, can influence these statistics.
top10onfansbasis= authors_clean.nlargest(10,'fans_count')
popular_author_names = top10onfansbasis['name'].tolist()
book_data_filtered = books2[books2['author_name'].isin(influential_author_names)]
book_data_filtered.head(2)
| title | num_pages | language | average_rating | ratings_count | text_reviews_count | author_name | original_publication_date | publication_date | format | series_id | series_name | series_position | time_gap | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 179294 | A Song for Lya | 208.0 | eng | 3.94 | 1787 | 154 | George R.R. Martin | 1976-02-01 | 1976-02-01 | Mass Market Paperback | NaT | |||
| 1183478 | Het stervende licht | 352.0 | nl | 3.57 | 5665 | 538 | George R.R. Martin | 1977-01-01 | 1977-01-01 | Paperback | 335 days |
here the Publication Date column has the value in wrong format, so we correct that area:
book_data_filtered["publication_date"] = pd.to_datetime(book_data_filtered["publication_date"], errors='coerce')
book_data_filtered["publication_date"] = pd.to_datetime(book_data_filtered["publication_date"])
present_date = datetime.now()
book_data_filtered = book_data_filtered[book_data_filtered['publication_date'] <= present_date]
book_data_filtered["publication_date"].max()
<ipython-input-153-bc5a032a9d9f>:1: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy book_data_filtered["publication_date"] = pd.to_datetime(book_data_filtered["publication_date"], errors='coerce') <ipython-input-153-bc5a032a9d9f>:2: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy book_data_filtered["publication_date"] = pd.to_datetime(book_data_filtered["publication_date"])
Timestamp('2021-03-02 00:00:00')
# we are sorting the DataFrame by 'publication_date' within each series
book_data_filtered = book_data_filtered.sort_values(by=['series_name', 'publication_date'])
# and then calculating time gap between subsequent publications
book_data_filtered['time_gap'] = book_data_filtered.groupby('series_name')['publication_date'].diff()
# the average time gap for books belonging to a series
avg_time_gap_within_series = book_data_filtered[book_data_filtered['series_name']!='']['time_gap'].mean()
# Calculate the average time gap for books not belonging to a series
avg_time_gap_not_in_series = book_data_filtered[book_data_filtered['series_name']=='']['time_gap'].mean()
print(f'Average time gap between two subsequent publications for a series of books is {avg_time_gap_within_series.days} days')
print(f'\nAverage time gap between two subsequent publications for books not belonging to a series is {avg_time_gap_not_in_series.days} days')
Average time gap between two subsequent publications for a series of books is 89 days Average time gap between two subsequent publications for books not belonging to a series is 8 days
# we get the publication year
book_data_filtered['publication_year'] = book_data_filtered['publication_date'].dt.year
# to count the cumulative number of books published after group by author and year
book_data_filtered['cumulative_books'] = book_data_filtered.groupby(['author_name', 'publication_year']).cumcount() + 1
book_data_filtered[['author_name','publication_year','cumulative_books']]
| author_name | publication_year | cumulative_books | |
|---|---|---|---|
| 179294 | George R.R. Martin | 1976 | 1 |
| 1183478 | George R.R. Martin | 1977 | 1 |
| 3942614 | George R.R. Martin | 1978 | 1 |
| 781039 | George R.R. Martin | 1978 | 2 |
| 486916 | George R.R. Martin | 1979 | 1 |
| ... | ... | ... | ... |
| 3422117 | Haruki Murakami | 2012 | 85 |
| 4710419 | Haruki Murakami | 2013 | 77 |
| 5498749 | Haruki Murakami | 2013 | 78 |
| 6101280 | Haruki Murakami | 2014 | 57 |
| 6447392 | Haruki Murakami | 2014 | 58 |
7156 rows × 3 columns
# Extract the year from the 'publication_date' and create a new column 'publication_year'
book_data_filtered['publication_year'] = book_data_filtered['publication_date'].dt.year
book_counts = book_data_filtered.groupby(['author_name', 'publication_year']).size().unstack(level=0, fill_value=0)
#the above line of code groups the data by author_name and publication_year unique combinations and then unstacks the resultant
# into separate columns of author_names and rows of publication_year. The author who has a book published in a given year will have a cell value 1, 2, 3...etc
# based on the number of books published by that author in that given year. I am using this unstack function of the pandas dataframe to store a df into
# the book_counts.
book_counts.head(5)
| author_name | Brandon Sanderson | Cassandra Clare | Diana Gabaldon | George R.R. Martin | Haruki Murakami | J.K. Rowling | James Patterson | Nicholas Sparks | Nora Roberts | Rick Riordan |
|---|---|---|---|---|---|---|---|---|---|---|
| publication_year | ||||||||||
| 1976 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1977 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1978 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1979 | 0 | 0 | 0 | 4 | 2 | 0 | 0 | 0 | 0 | 0 |
| 1980 | 0 | 0 | 0 | 2 | 1 | 0 | 1 | 0 | 0 | 0 |
cumulative_counts = book_counts.cumsum()
cumulative_counts.head(5)
| author_name | Brandon Sanderson | Cassandra Clare | Diana Gabaldon | George R.R. Martin | Haruki Murakami | J.K. Rowling | James Patterson | Nicholas Sparks | Nora Roberts | Rick Riordan |
|---|---|---|---|---|---|---|---|---|---|---|
| publication_year | ||||||||||
| 1976 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1977 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1978 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1979 | 0 | 0 | 0 | 9 | 2 | 0 | 0 | 0 | 0 | 0 |
| 1980 | 0 | 0 | 0 | 11 | 3 | 0 | 1 | 0 | 0 | 0 |
The cumsum() function helped in calculating the cumulative number of books published by the author upto a certain year. For example, George RR Martin has 2 books published till 1976, 2+1 till 1977, 2+1+2=5 till 1978 and so on...
# then we plot the cumulative counts for each author
cumulative_counts.plot(figsize=(10,5))
plt.title('Cumulative Number of Books Published by Author per Year')
plt.xlabel('Year')
plt.ylabel('Cumulative Number of Books')
plt.legend(title='Author')
plt.grid()
years = cumulative_counts.index
year_step = 3
years_to_display = years[::year_step]
plt.xticks(years_to_display)
plt.show()
Looking at the graph, we can infer that, these top 10 popular authors are contemporary to each other. Their production curve has a sharp rise somewhere between 2009 and 2015 and after 2015, the production rate curve flattens. We can say, between approximately 2009 and 2015, their production rate was higher.
Question 1
import json
import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
booko= pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", nrows=10, lines= True)
booko
| id | title | authors | author_name | author_id | work_id | isbn | isbn13 | asin | language | average_rating | rating_dist | ratings_count | text_reviews_count | publication_date | original_publication_date | format | edition_information | image_url | publisher | num_pages | series_id | series_name | series_position | shelves | description | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2 | Harry Potter and the Order of the Phoenix (Har... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 2809203 | 0439358078 | 9780439358071 | eng | 4.50 | 5:1674064|4:664833|3:231195|2:41699|1:16215|to... | 2628006 | 44716 | 2004-09 | 2003-06-21 | Paperback | US Edition | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic Inc. | 870 | 45175 | Harry Potter | 5 | [{'name': 'to-read', 'count': 324191}, {'name'... | There is a door at the end of a silent corrido... | |
| 1 | 3 | Harry Potter and the Sorcerer's Stone (Harry P... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 4640799 | eng | 4.48 | 5:4801606|4:1681521|3:623286|2:145898|1:125040... | 7377351 | 116930 | 2003-11-01 | 1997-06-26 | Hardcover | Library Edition | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic Inc | 309 | 45175 | Harry Potter | 1 | [{'name': 'fantasy', 'count': 63540}, {'name':... | Harry Potter's life is miserable. His parents ... | |||
| 2 | 4 | Harry Potter and the Chamber of Secrets (Harry... | None | J.K. Rowling | 1077326 | 6231171 | 0439554896 | 9780439554893 | eng | 4.43 | 5:1690166|4:781011|3:313727|2:54687|1:15453|to... | 2855044 | 55286 | 2003-11-01 | 1998-07-02 | Hardcover | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 352 | 45175 | Harry Potter | 2 | [{'name': 'to-read', 'count': 282341}, {'name'... | The Dursleys were so mean and hideous that sum... | ||
| 3 | 5 | Harry Potter and the Prisoner of Azkaban (Harr... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 2402163 | 043965548X | 9780439655484 | eng | 4.57 | 5:1994597|4:696545|3:212678|2:28915|1:13959|to... | 2946694 | 58023 | 2004-05-01 | 1999-07-08 | Mass Market Paperback | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic Inc. | 435 | 45175 | Harry Potter | 3 | [{'name': 'to-read', 'count': 292815}, {'name'... | For twelve long years, the dread fortress of A... | ||
| 4 | 6 | Harry Potter and the Goblet of Fire (Harry Pot... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 3046572 | eng | 4.56 | 5:1808039|4:663849|3:193604|2:27759|1:12425|to... | 2705676 | 48637 | 2002-09-28 | 2000-07-08 | Paperback | First Scholastic Trade Paperback Edition | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 734 | 45175 | Harry Potter | 4 | [{'name': 'to-read', 'count': 287086}, {'name'... | Harry Potter is midway through his training as... | |||
| 5 | 7 | The Harry Potter Collection (Harry Potter, #1-6) | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 21457570 | 0439887453 | 9780439887458 | eng | 4.73 | 5:25063|4:4467|3:1103|2:227|1:282|total:31142 | 31142 | 975 | 2006-09-01 | 2005-01-01 | Paperback | Box Set | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 45175 | Harry Potter | 1-6 | [{'name': 'to-read', 'count': 5809}, {'name': ... | <div>Six years of magic, adventure, and myster... | ||
| 6 | 8 | Harry Potter Boxed Set, Books 1-5 (Harry Potte... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 21457576 | 0439682584 | 9780439682589 | eng | 4.79 | 5:49438|4:6112|3:1525|2:354|1:534|total:57963 | 57963 | 183 | 2004-09-13 | 2003-10-01 | Paperback | https://s.gr-assets.com/assets/nophoto/book/11... | Scholastic | 2690 | [{'name': 'to-read', 'count': 7030}, {'name': ... | Box Set containing Harry Potter and the Sorcer... | |||||
| 7 | 10 | Harry Potter Collection (Harry Potter, #1-6) | None | J.K. Rowling | 1077326 | 21457570 | 0439827604 | 9780439827607 | eng | 4.73 | 5:25063|4:4467|3:1103|2:227|1:282|total:31142 | 31142 | 975 | 2005-09-12 | 2005-01-01 | Hardcover | Box Set | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 3342 | 45175 | Harry Potter | 1-6 | [{'name': 'to-read', 'count': 5809}, {'name': ... | Six years of magic, adventure, and mystery mak... | |
| 8 | 11 | The Hitchhiker's Guide to the Galaxy (Hitchhik... | None | Douglas Adams | 4 | 3078186 | eng | 4.22 | 5:753962|4:436665|3:206876|2:60681|1:32955|tot... | 1491139 | 31417 | 2005 | 1979-10-12 | Mass Market Paperback | Movie Tie-In Edition | https://i.gr-assets.com/images/S/compressed.ph... | Del Rey Books | 216 | 40957 | The Hitchhiker's Guide to the Galaxy | 1 | [{'name': 'to-read', 'count': 716080}, {'name'... | Seconds before the Earth is demolished to make... | |||
| 9 | 12 | The Ultimate Hitchhiker's Guide: Five Complete... | None | Douglas Adams | 4 | 135328 | 0517226952 | 9780517226957 | eng | 4.36 | 5:167705|4:81013|3:32283|2:8665|1:4360|total:2... | 294026 | 5429 | 2005-11-01 | 1996-01-17 | Leather Bound | https://i.gr-assets.com/images/S/compressed.ph... | Gramercy Books | 815 | 40957 | The Hitchhiker's Guide to the Galaxy | 0.5-5 | [{'name': 'to-read', 'count': 128191}, {'name'... | At last in paperback in one complete volume, h... |
booko['rating_dist']
0 5:1674064|4:664833|3:231195|2:41699|1:16215|to... 1 5:4801606|4:1681521|3:623286|2:145898|1:125040... 2 5:1690166|4:781011|3:313727|2:54687|1:15453|to... 3 5:1994597|4:696545|3:212678|2:28915|1:13959|to... 4 5:1808039|4:663849|3:193604|2:27759|1:12425|to... 5 5:25063|4:4467|3:1103|2:227|1:282|total:31142 6 5:49438|4:6112|3:1525|2:354|1:534|total:57963 7 5:25063|4:4467|3:1103|2:227|1:282|total:31142 8 5:753962|4:436665|3:206876|2:60681|1:32955|tot... 9 5:167705|4:81013|3:32283|2:8665|1:4360|total:2... Name: rating_dist, dtype: object
def createcounter(x):
listo= x.split("|") # make a list of the individual ratings
my_dict= {}
for s in listo:
key, value = s.split(':') #split each rating into key and value(was string before)
my_dict[key] = int(value)# make a dictionnary out of it
countocount= 0
if my_dict['5']/ my_dict['total']> 0.3:
countocount+=1 #The books that have achieved more than 30% ratings above 4 will get marked with a 1, the others with a 0
return countocount
chunksize = 10**5
sicount=0 #Variable to count the number of books with more than 30% ratings above 4
universe = 0 #Variable to count the number of rated books in total
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize,lines=True ):
chunk = chunk[chunk["ratings_count"] > 0 ]#Includes only the rows in chunk, that have ratings
universe += len(chunk) #number of rows that the chunk contains
chunk["siono"] = chunk.apply(lambda row: createcounter(row["rating_dist"]), axis=1) #Calls the function createcounter for every single row in the chunk and stores the value 1 or in a new column 'siono'
sicount += len(chunk[chunk["siono"] == 1 ]) # number of rows in the chunk, with more than 30% ratings above 4
print(sicount/universe) #probability that a book has over 30% of the ratings above 4
0.5221711201578421
Question 2
# Estimate the probability that an author publishes a new book within two years from its last work.
# Assumptions:
#-If a book is published in a new format it is considered as new publication
#-Also a series of books is considered as new publication
import json
import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
from collections import defaultdict
from datetime import datetime
from statistics import mean
booko2= pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", nrows=10, lines= True)
booko2
| id | title | authors | author_name | author_id | work_id | isbn | isbn13 | asin | language | average_rating | rating_dist | ratings_count | text_reviews_count | publication_date | original_publication_date | format | edition_information | image_url | publisher | num_pages | series_id | series_name | series_position | shelves | description | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2 | Harry Potter and the Order of the Phoenix (Har... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 2809203 | 0439358078 | 9780439358071 | eng | 4.50 | 5:1674064|4:664833|3:231195|2:41699|1:16215|to... | 2628006 | 44716 | 2004-09 | 2003-06-21 | Paperback | US Edition | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic Inc. | 870 | 45175 | Harry Potter | 5 | [{'name': 'to-read', 'count': 324191}, {'name'... | There is a door at the end of a silent corrido... | |
| 1 | 3 | Harry Potter and the Sorcerer's Stone (Harry P... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 4640799 | eng | 4.48 | 5:4801606|4:1681521|3:623286|2:145898|1:125040... | 7377351 | 116930 | 2003-11-01 | 1997-06-26 | Hardcover | Library Edition | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic Inc | 309 | 45175 | Harry Potter | 1 | [{'name': 'fantasy', 'count': 63540}, {'name':... | Harry Potter's life is miserable. His parents ... | |||
| 2 | 4 | Harry Potter and the Chamber of Secrets (Harry... | None | J.K. Rowling | 1077326 | 6231171 | 0439554896 | 9780439554893 | eng | 4.43 | 5:1690166|4:781011|3:313727|2:54687|1:15453|to... | 2855044 | 55286 | 2003-11-01 | 1998-07-02 | Hardcover | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 352 | 45175 | Harry Potter | 2 | [{'name': 'to-read', 'count': 282341}, {'name'... | The Dursleys were so mean and hideous that sum... | ||
| 3 | 5 | Harry Potter and the Prisoner of Azkaban (Harr... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 2402163 | 043965548X | 9780439655484 | eng | 4.57 | 5:1994597|4:696545|3:212678|2:28915|1:13959|to... | 2946694 | 58023 | 2004-05-01 | 1999-07-08 | Mass Market Paperback | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic Inc. | 435 | 45175 | Harry Potter | 3 | [{'name': 'to-read', 'count': 292815}, {'name'... | For twelve long years, the dread fortress of A... | ||
| 4 | 6 | Harry Potter and the Goblet of Fire (Harry Pot... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 3046572 | eng | 4.56 | 5:1808039|4:663849|3:193604|2:27759|1:12425|to... | 2705676 | 48637 | 2002-09-28 | 2000-07-08 | Paperback | First Scholastic Trade Paperback Edition | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 734 | 45175 | Harry Potter | 4 | [{'name': 'to-read', 'count': 287086}, {'name'... | Harry Potter is midway through his training as... | |||
| 5 | 7 | The Harry Potter Collection (Harry Potter, #1-6) | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 21457570 | 0439887453 | 9780439887458 | eng | 4.73 | 5:25063|4:4467|3:1103|2:227|1:282|total:31142 | 31142 | 975 | 2006-09-01 | 2005-01-01 | Paperback | Box Set | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 45175 | Harry Potter | 1-6 | [{'name': 'to-read', 'count': 5809}, {'name': ... | <div>Six years of magic, adventure, and myster... | ||
| 6 | 8 | Harry Potter Boxed Set, Books 1-5 (Harry Potte... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 21457576 | 0439682584 | 9780439682589 | eng | 4.79 | 5:49438|4:6112|3:1525|2:354|1:534|total:57963 | 57963 | 183 | 2004-09-13 | 2003-10-01 | Paperback | https://s.gr-assets.com/assets/nophoto/book/11... | Scholastic | 2690 | [{'name': 'to-read', 'count': 7030}, {'name': ... | Box Set containing Harry Potter and the Sorcer... | |||||
| 7 | 10 | Harry Potter Collection (Harry Potter, #1-6) | None | J.K. Rowling | 1077326 | 21457570 | 0439827604 | 9780439827607 | eng | 4.73 | 5:25063|4:4467|3:1103|2:227|1:282|total:31142 | 31142 | 975 | 2005-09-12 | 2005-01-01 | Hardcover | Box Set | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 3342 | 45175 | Harry Potter | 1-6 | [{'name': 'to-read', 'count': 5809}, {'name': ... | Six years of magic, adventure, and mystery mak... | |
| 8 | 11 | The Hitchhiker's Guide to the Galaxy (Hitchhik... | None | Douglas Adams | 4 | 3078186 | eng | 4.22 | 5:753962|4:436665|3:206876|2:60681|1:32955|tot... | 1491139 | 31417 | 2005 | 1979-10-12 | Mass Market Paperback | Movie Tie-In Edition | https://i.gr-assets.com/images/S/compressed.ph... | Del Rey Books | 216 | 40957 | The Hitchhiker's Guide to the Galaxy | 1 | [{'name': 'to-read', 'count': 716080}, {'name'... | Seconds before the Earth is demolished to make... | |||
| 9 | 12 | The Ultimate Hitchhiker's Guide: Five Complete... | None | Douglas Adams | 4 | 135328 | 0517226952 | 9780517226957 | eng | 4.36 | 5:167705|4:81013|3:32283|2:8665|1:4360|total:2... | 294026 | 5429 | 2005-11-01 | 1996-01-17 | Leather Bound | https://i.gr-assets.com/images/S/compressed.ph... | Gramercy Books | 815 | 40957 | The Hitchhiker's Guide to the Galaxy | 0.5-5 | [{'name': 'to-read', 'count': 128191}, {'name'... | At last in paperback in one complete volume, h... |
grouped = booko2.groupby('author_id')['original_publication_date']
grouped
author_dict = grouped.apply(list).to_dict()
author_dict
{4: ['1979-10-12', '1996-01-17'],
1077326: ['2003-06-21',
'1997-06-26',
'1998-07-02',
'1999-07-08',
'2000-07-08',
'2005-01-01',
'2003-10-01',
'2005-01-01']}
chunksize= 10**4
chunks=[]
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize, lines=True):
chunks.append(chunk[['author_id', 'original_publication_date']])
df = pd.concat(chunks, axis=0)
grouped = df.groupby('author_id')['original_publication_date'] #selects all the books with the same author and stores the original publication dates in a list
author_dict = grouped.apply(list).to_dict() # make a dictionnary out of it
authorslonger2= 0 #Count for authors that had longer than 2 years on average to publish a new book
authorsfaster2=0 ##Count for authors that were faster than 2 years on average to publish a new book
for author_id, original_publication_date in author_dict.items():
try:
original_publication_date = sorted([datetime.strptime(date, '%Y-%m-%d') for date in original_publication_date if date is not None]) #convert them to datetime objects
except ValueError:
continue # If the convertion can't be done the author is skipped
differences = [] # Variable to calculate the difference between the the publications of an author
differences_auth=[] # Variable to calculate the average calculation time of the authors
for i in range(len(original_publication_date)-1):
try:
difference = original_publication_date[i+1] - original_publication_date[i]
differences.append(difference.total_seconds()/(3600*24*360))
except TypeError: # If the calculation can't be done the author is skipped
continue
if differences: # Handling the exception of an empty list
average_difference = mean(differences)
if average_difference >= 2:
authorslonger2 += 1
if average_difference <= 2:
authorsfaster2 += 1
else:
continue
prob_faster2= authorsfaster2/(authorslonger2+authorsfaster2)
print(prob_faster2)
0.8973156401944895
Question 3
import json
import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
booko2= pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", nrows=10, lines= True)
booko2
| id | title | authors | author_name | author_id | work_id | isbn | isbn13 | asin | language | average_rating | rating_dist | ratings_count | text_reviews_count | publication_date | original_publication_date | format | edition_information | image_url | publisher | num_pages | series_id | series_name | series_position | shelves | description | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2 | Harry Potter and the Order of the Phoenix (Har... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 2809203 | 0439358078 | 9780439358071 | eng | 4.50 | 5:1674064|4:664833|3:231195|2:41699|1:16215|to... | 2628006 | 44716 | 2004-09 | 2003-06-21 | Paperback | US Edition | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic Inc. | 870 | 45175 | Harry Potter | 5 | [{'name': 'to-read', 'count': 324191}, {'name'... | There is a door at the end of a silent corrido... | |
| 1 | 3 | Harry Potter and the Sorcerer's Stone (Harry P... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 4640799 | eng | 4.48 | 5:4801606|4:1681521|3:623286|2:145898|1:125040... | 7377351 | 116930 | 2003-11-01 | 1997-06-26 | Hardcover | Library Edition | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic Inc | 309 | 45175 | Harry Potter | 1 | [{'name': 'fantasy', 'count': 63540}, {'name':... | Harry Potter's life is miserable. His parents ... | |||
| 2 | 4 | Harry Potter and the Chamber of Secrets (Harry... | None | J.K. Rowling | 1077326 | 6231171 | 0439554896 | 9780439554893 | eng | 4.43 | 5:1690166|4:781011|3:313727|2:54687|1:15453|to... | 2855044 | 55286 | 2003-11-01 | 1998-07-02 | Hardcover | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 352 | 45175 | Harry Potter | 2 | [{'name': 'to-read', 'count': 282341}, {'name'... | The Dursleys were so mean and hideous that sum... | ||
| 3 | 5 | Harry Potter and the Prisoner of Azkaban (Harr... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 2402163 | 043965548X | 9780439655484 | eng | 4.57 | 5:1994597|4:696545|3:212678|2:28915|1:13959|to... | 2946694 | 58023 | 2004-05-01 | 1999-07-08 | Mass Market Paperback | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic Inc. | 435 | 45175 | Harry Potter | 3 | [{'name': 'to-read', 'count': 292815}, {'name'... | For twelve long years, the dread fortress of A... | ||
| 4 | 6 | Harry Potter and the Goblet of Fire (Harry Pot... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 3046572 | eng | 4.56 | 5:1808039|4:663849|3:193604|2:27759|1:12425|to... | 2705676 | 48637 | 2002-09-28 | 2000-07-08 | Paperback | First Scholastic Trade Paperback Edition | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 734 | 45175 | Harry Potter | 4 | [{'name': 'to-read', 'count': 287086}, {'name'... | Harry Potter is midway through his training as... | |||
| 5 | 7 | The Harry Potter Collection (Harry Potter, #1-6) | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 21457570 | 0439887453 | 9780439887458 | eng | 4.73 | 5:25063|4:4467|3:1103|2:227|1:282|total:31142 | 31142 | 975 | 2006-09-01 | 2005-01-01 | Paperback | Box Set | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 45175 | Harry Potter | 1-6 | [{'name': 'to-read', 'count': 5809}, {'name': ... | <div>Six years of magic, adventure, and myster... | ||
| 6 | 8 | Harry Potter Boxed Set, Books 1-5 (Harry Potte... | [{'id': '1077326', 'name': 'J.K. Rowling', 'ro... | J.K. Rowling | 1077326 | 21457576 | 0439682584 | 9780439682589 | eng | 4.79 | 5:49438|4:6112|3:1525|2:354|1:534|total:57963 | 57963 | 183 | 2004-09-13 | 2003-10-01 | Paperback | https://s.gr-assets.com/assets/nophoto/book/11... | Scholastic | 2690 | [{'name': 'to-read', 'count': 7030}, {'name': ... | Box Set containing Harry Potter and the Sorcer... | |||||
| 7 | 10 | Harry Potter Collection (Harry Potter, #1-6) | None | J.K. Rowling | 1077326 | 21457570 | 0439827604 | 9780439827607 | eng | 4.73 | 5:25063|4:4467|3:1103|2:227|1:282|total:31142 | 31142 | 975 | 2005-09-12 | 2005-01-01 | Hardcover | Box Set | https://i.gr-assets.com/images/S/compressed.ph... | Scholastic | 3342 | 45175 | Harry Potter | 1-6 | [{'name': 'to-read', 'count': 5809}, {'name': ... | Six years of magic, adventure, and mystery mak... | |
| 8 | 11 | The Hitchhiker's Guide to the Galaxy (Hitchhik... | None | Douglas Adams | 4 | 3078186 | eng | 4.22 | 5:753962|4:436665|3:206876|2:60681|1:32955|tot... | 1491139 | 31417 | 2005 | 1979-10-12 | Mass Market Paperback | Movie Tie-In Edition | https://i.gr-assets.com/images/S/compressed.ph... | Del Rey Books | 216 | 40957 | The Hitchhiker's Guide to the Galaxy | 1 | [{'name': 'to-read', 'count': 716080}, {'name'... | Seconds before the Earth is demolished to make... | |||
| 9 | 12 | The Ultimate Hitchhiker's Guide: Five Complete... | None | Douglas Adams | 4 | 135328 | 0517226952 | 9780517226957 | eng | 4.36 | 5:167705|4:81013|3:32283|2:8665|1:4360|total:2... | 294026 | 5429 | 2005-11-01 | 1996-01-17 | Leather Bound | https://i.gr-assets.com/images/S/compressed.ph... | Gramercy Books | 815 | 40957 | The Hitchhiker's Guide to the Galaxy | 0.5-5 | [{'name': 'to-read', 'count': 128191}, {'name'... | At last in paperback in one complete volume, h... |
booko3=pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/archive/list.json/list.json", nrows=10, lines=True)
booko3
| id | title | description | description_html | num_pages | num_books | num_voters | created_date | tags | num_likes | created_by | num_comments | books | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2 | The Worst Books of All Time | What do you think are the worst books ever wri... | \n What do you think are the worst books ... | 74 | 7395 | 18260 | May 20th, 2008 | [abominable, abomination, awful, bad, disgusti... | 175 | {'name': 'Michael Economy', 'id': '73'} | 2570 | [{'book_id': '41865', 'title': 'Twilight', 'au... |
| 1 | 3 | Best Science Fiction & Fantasy Books | Anything in the science fiction or fantasy gen... | \n Anything in the science fiction or fan... | 71 | 7023 | 21747 | May 29th, 2008 | [best-fantasy, best-science-fiction, earliest-... | 2989 | {'name': 'deleted user', 'id': ''} | 307 | [{'book_id': '375802', 'title': 'Ender's Game'... |
| 2 | 4 | Best Books of 2008 | The best books first published during 2008.See... | \n The best books first published during ... | 17 | 1678 | 6939 | May 29th, 2008 | [2008, best, by-year, earliest-list, fiction, ... | 59 | {'name': 'deleted user', 'id': ''} | 181 | [{'book_id': '2767052', 'title': 'The Hunger G... |
| 3 | 5 | Best Books of the Decade: 2000s | The best books published during the 2000s deca... | \n The best books published during the 20... | 70 | 6919 | 28249 | May 29th, 2008 | [2000, 2001, 2002, 2003, 2004, 2005, 2006, 200... | 1192 | {'name': 'deleted user', 'id': ''} | 163 | [{'book_id': '136251', 'title': 'Harry Potter ... |
| 4 | 6 | Best Books of the 20th Century | The best books published during the 20th centu... | \n The best books published during the 20... | 76 | 7600 | 49437 | May 29th, 2008 | [20th, 20th-century, best, by-century, by-year... | 6083 | {'name': 'deleted user', 'id': ''} | 510 | [{'book_id': '2657', 'title': 'To Kill a Mocki... |
| 5 | 7 | Best Books of the 21st Century | The best books published during the 21st centu... | \n The best books published during the 21... | 91 | 9032 | 21393 | May 29th, 2008 | [2001, 2002, 2003, 2004, 2005, 2006, 2007, 200... | 2024 | {'name': 'deleted user', 'id': ''} | 280 | [{'book_id': '136251', 'title': 'Harry Potter ... |
| 6 | 8 | Thickest Books Ever | Original novel, not omnibus editions.500 pages... | \n Original novel, not omnibus editions.<... | 9 | 862 | 2602 | June 4th, 2008 | [500-pages, 500-pages-plus, big-books, earlies... | 118 | {'name': 'Michael Economy', 'id': '73'} | 104 | [{'book_id': '6', 'title': 'Harry Potter and t... |
| 7 | 9 | Best Books of the Decade: 1980s | The best books published during the 1980s deca... | \n The best books published during the 19... | 21 | 2059 | 2323 | June 6th, 2008 | [1980, 1980s, 1981, 1982, 1983, 1984, 1985, 19... | 240 | {'name': 'deleted user', 'id': ''} | 41 | [{'book_id': '38447', 'title': 'The Handmaid's... |
| 8 | 10 | Best books for an African Safari | Best books to read on an African Safari. Books... | \n Best books to read on an African Safar... | 5 | 445 | 705 | June 9th, 2008 | [africa, african, earliest-list, location, saf... | 103 | {'name': 'deleted user', 'id': ''} | 9 | [{'book_id': '7244', 'title': 'The Poisonwood ... |
| 9 | 11 | Best Crime & Mystery Books | The best of crime and mystery books.If the boo... | \n The best of crime and mystery books.<b... | 62 | 6112 | 14241 | June 10th, 2008 | [best, crime, crime-mystery, mystery] | 1827 | {'name': 'deleted user', 'id': ''} | 138 | [{'book_id': '2429135', 'title': 'The Girl wit... |
value2 = booko3.loc[0, 'books']
value2
[{'book_id': '41865',
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{'book_id': '1162543',
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{'book_id': '49041',
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{'book_id': '428263',
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{'book_id': '10818853',
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{'book_id': '6263078',
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{'book_id': '6076107',
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{'book_id': '3090465',
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{'book_id': '968',
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{'book_id': '4013201',
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{'book_id': '1812457',
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{'book_id': '48625',
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{'book_id': '19501',
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{'book_id': '7937462',
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{'book_id': '9742',
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{'book_id': '7455',
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{'book_id': '5107',
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{'book_id': '240469',
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{'book_id': '119322',
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{'book_id': '8714',
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{'book_id': '8752457',
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{'book_id': '11857408',
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{'book_id': '675626',
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{'book_id': '6411961',
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{'book_id': '7613',
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{'book_id': '9416',
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{'book_id': '3268926',
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{'book_id': '252914',
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{'book_id': '13536860',
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{'book_id': '35220',
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{'book_id': '6867',
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{'book_id': '56495',
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{'book_id': '3636',
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{'book_id': '2657',
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{'book_id': '703847',
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{'book_id': '252917',
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{'book_id': '6487308',
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{'book_id': '13079982',
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{'book_id': '801178',
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'position': {'ranking': 915, 'score': 395, 'votes': 4}},
{'book_id': '5176',
'title': 'While I Was Gone',
'author_id': '3517',
'author': 'Sue Miller',
'position': {'ranking': 916, 'score': 395, 'votes': 4}},
{'book_id': '88077',
'title': 'The Magic Mountain',
'author_id': '19405',
'author': 'Thomas Mann',
'position': {'ranking': 917, 'score': 395, 'votes': 4}},
{'book_id': '105578',
'title': 'One Night at the Call Center',
'author_id': '61124',
'author': 'Chetan Bhagat',
'position': {'ranking': 918, 'score': 395, 'votes': 4}},
{'book_id': '2520383',
'title': 'The Rose Labyrinth',
'author_id': '29554',
'author': 'Titania Hardie',
'position': {'ranking': 919, 'score': 395, 'votes': 4}},
{'book_id': '31463',
'title': 'Far From the Madding Crowd',
'author_id': '15905',
'author': 'Thomas Hardy',
'position': {'ranking': 920, 'score': 394, 'votes': 5}},
{'book_id': '6401',
'title': 'Prophecy: What the Future Holds for You',
'author_id': '4333',
'author': 'Sylvia Browne',
'position': {'ranking': 921, 'score': 394, 'votes': 7}},
{'book_id': '1829655',
'title': "The Demon's Lexicon",
'author_id': '836009',
'author': 'Sarah Rees Brennan',
'position': {'ranking': 922, 'score': 394, 'votes': 5}},
{'book_id': '59716',
'title': 'To the Lighthouse',
'author_id': '6765',
'author': 'Virginia Woolf',
'position': {'ranking': 923, 'score': 394, 'votes': 6}},
{'book_id': '16068905',
'title': 'Fangirl',
'author_id': '4208569',
'author': 'Rainbow Rowell',
'position': {'ranking': 924, 'score': 394, 'votes': 4}},
{'book_id': '770303',
'title': 'Juventud en éxtasis',
'author_id': '86285',
'author': 'Carlos Cuauhtémoc Sánchez',
'position': {'ranking': 925, 'score': 393, 'votes': 4}},
{'book_id': '1476261',
'title': 'Girls of Riyadh',
'author_id': '4415675',
'author': 'Rajaa Alsanea',
'position': {'ranking': 926, 'score': 393, 'votes': 4}},
{'book_id': '5091',
'title': 'The Dark Tower',
'author_id': '3389',
'author': 'Stephen King',
'position': {'ranking': 927, 'score': 393, 'votes': 4}},
{'book_id': '29653134',
'title': 'شرح رواية أنتيخريستوس - التحليل والمصادر',
'author_id': '8473982',
'author': 'أحمد خالد مصطفى',
'position': {'ranking': 928, 'score': 393, 'votes': 4}},
{'book_id': '13517535',
'title': 'Thoughtless',
'author_id': '4372391',
'author': 'S.C. Stephens',
'position': {'ranking': 929, 'score': 392, 'votes': 4}},
{'book_id': '34039540',
'title': 'ليالي الجحيم',
'author_id': '8473982',
'author': 'أحمد خالد مصطفى',
'position': {'ranking': 930, 'score': 392, 'votes': 4}},
{'book_id': '761575',
'title': 'House Atreides',
'author_id': '56',
'author': 'Brian Herbert',
'position': {'ranking': 931, 'score': 391, 'votes': 5}},
{'book_id': '6644117',
'title': 'The Iron King',
'author_id': '2995873',
'author': 'Julie Kagawa',
'position': {'ranking': 932, 'score': 391, 'votes': 4}},
{'book_id': '6976',
'title': 'The Mermaid Chair',
'author_id': '4711',
'author': 'Sue Monk Kidd',
'position': {'ranking': 933, 'score': 391, 'votes': 4}},
{'book_id': '24100',
'title': 'The Golden Notebook',
'author_id': '7728',
'author': 'Doris Lessing',
'position': {'ranking': 934, 'score': 390, 'votes': 4}},
{'book_id': '62032',
'title': 'The 13½ Lives of Captain Bluebear',
'author_id': '34878',
'author': 'Walter Moers',
'position': {'ranking': 935, 'score': 390, 'votes': 4}},
{'book_id': '6425',
'title': 'Hard Eight',
'author_id': '2384',
'author': 'Janet Evanovich',
'position': {'ranking': 936, 'score': 390, 'votes': 5}},
{'book_id': '7920450',
'title': 'Comfort Food',
'author_id': '2654606',
'author': 'Kitty Thomas',
'position': {'ranking': 937, 'score': 390, 'votes': 4}},
{'book_id': '23766634',
'title': 'A Court of Wings and Ruin',
'author_id': '3433047',
'author': 'Sarah J. Maas',
'position': {'ranking': 938, 'score': 390, 'votes': 5}},
{'book_id': '43566744',
'title': 'ملائك نصيبين',
'author_id': '8473982',
'author': 'أحمد خالد مصطفى',
'position': {'ranking': 939, 'score': 390, 'votes': 4}},
{'book_id': '7572',
'title': 'Even Cowgirls Get the Blues',
'author_id': '197',
'author': 'Tom Robbins',
'position': {'ranking': 940, 'score': 389, 'votes': 5}},
{'book_id': '3087',
'title': 'A Room with a View',
'author_id': '86404',
'author': 'E.M. Forster',
'position': {'ranking': 941, 'score': 389, 'votes': 5}},
{'book_id': '65057',
'title': 'A Good Dog: The Story of Orson, Who Changed My Life',
'author_id': '36719',
'author': 'Jon Katz',
'position': {'ranking': 942, 'score': 389, 'votes': 4}},
{'book_id': '1736739',
'title': 'Olive Kitteridge',
'author_id': '97313',
'author': 'Elizabeth Strout',
'position': {'ranking': 943, 'score': 389, 'votes': 4}},
{'book_id': '251688',
'title': "Breakfast at Tiffany's and Three Stories",
'author_id': '431149',
'author': 'Truman Capote',
'position': {'ranking': 944, 'score': 388, 'votes': 4}},
{'book_id': '11691',
'title': 'Snow',
'author_id': '1728',
'author': 'Orhan Pamuk',
'position': {'ranking': 945, 'score': 388, 'votes': 4}},
{'book_id': '23009428',
'title': 'سلسلة الشيطان يحكي - العدد الأول: مطعم اللحوم البشرية',
'author_id': '8473982',
'author': 'أحمد خالد مصطفى',
'position': {'ranking': 946, 'score': 388, 'votes': 4}},
{'book_id': '405999',
'title': 'Confessions of a Sociopathic Social Climber: The Katya Livingston Chronicles',
'author_id': '4636148',
'author': 'Adèle Lang',
'position': {'ranking': 947, 'score': 387, 'votes': 5}},
{'book_id': '67238',
'title': 'Dead Poets Society',
'author_id': '52601',
'author': 'N.H. Kleinbaum',
'position': {'ranking': 948, 'score': 386, 'votes': 4}},
{'book_id': '668608',
'title': 'Ghostwalk',
'author_id': '76199',
'author': 'Rebecca Stott',
'position': {'ranking': 949, 'score': 386, 'votes': 4}},
{'book_id': '6614',
'title': 'Lipstick Jungle',
'author_id': '4415',
'author': 'Candace Bushnell',
'position': {'ranking': 950, 'score': 386, 'votes': 5}},
{'book_id': '18943',
'title': 'Confessions of an Ugly Stepsister',
'author_id': '7025',
'author': 'Gregory Maguire',
'position': {'ranking': 951, 'score': 386, 'votes': 5}},
{'book_id': '41667',
'title': 'My Side of the Mountain',
'author_id': '23509',
'author': 'Jean Craighead George',
'position': {'ranking': 952, 'score': 386, 'votes': 4}},
{'book_id': '13497818',
'title': 'The Casual Vacancy',
'author_id': '1077326',
'author': 'J.K. Rowling',
'position': {'ranking': 953, 'score': 386, 'votes': 4}},
{'book_id': '5168',
'title': 'Where the Heart Is',
'author_id': '3510',
'author': 'Billie Letts',
'position': {'ranking': 954, 'score': 384, 'votes': 4}},
{'book_id': '13262783',
'title': 'Every Day',
'author_id': '11664',
'author': 'David Levithan',
'position': {'ranking': 955, 'score': 384, 'votes': 4}},
{'book_id': '28866',
'title': 'Dark Prince',
'author_id': '6268',
'author': 'Christine Feehan',
'position': {'ranking': 956, 'score': 384, 'votes': 4}},
{'book_id': '5171894',
'title': 'The Doomsday Key',
'author_id': '38809',
'author': 'James Rollins',
'position': {'ranking': 957, 'score': 384, 'votes': 4}},
{'book_id': '7619292',
'title': 'Twilight: The Graphic Novel, Vol. 1',
'author_id': '4379470',
'author': 'Young Kim',
'position': {'ranking': 958, 'score': 383, 'votes': 5}},
{'book_id': '5797',
'title': 'Vanity Fair',
'author_id': '3953',
'author': 'William Makepeace Thackeray',
'position': {'ranking': 959, 'score': 382, 'votes': 4}},
{'book_id': '50840',
'title': "Farnham's Freehold",
'author_id': '205',
'author': 'Robert A. Heinlein',
'position': {'ranking': 960, 'score': 382, 'votes': 5}},
{'book_id': '38913',
'title': 'Follow Your Heart',
'author_id': '21930',
'author': 'Susanna Tamaro',
'position': {'ranking': 961, 'score': 382, 'votes': 4}},
{'book_id': '22328',
'title': 'Neuromancer',
'author_id': '9226',
'author': 'William Gibson',
'position': {'ranking': 962, 'score': 382, 'votes': 4}},
{'book_id': '7082',
'title': 'Do Androids Dream of Electric Sheep?',
'author_id': '4764',
'author': 'Philip K. Dick',
'position': {'ranking': 963, 'score': 381, 'votes': 4}},
{'book_id': '5368',
'title': 'Forever Amber',
'author_id': '3620',
'author': 'Kathleen Winsor',
'position': {'ranking': 964, 'score': 380, 'votes': 4}},
{'book_id': '228534',
'title': 'The Weight of Water',
'author_id': '3530',
'author': 'Anita Shreve',
'position': {'ranking': 965, 'score': 380, 'votes': 4}},
{'book_id': '56759',
'title': 'The Mayor of Casterbridge',
'author_id': '15905',
'author': 'Thomas Hardy',
'position': {'ranking': 966, 'score': 380, 'votes': 5}},
{'book_id': '10619',
'title': 'Rose Madder',
'author_id': '3389',
'author': 'Stephen King',
'position': {'ranking': 967, 'score': 380, 'votes': 4}},
{'book_id': '33600',
'title': 'Shantaram',
'author_id': '18907',
'author': 'Gregory David Roberts',
'position': {'ranking': 968, 'score': 380, 'votes': 4}},
{'book_id': '257837',
'title': 'Shane',
'author_id': '150701',
'author': 'Jack Schaefer',
'position': {'ranking': 969, 'score': 379, 'votes': 5}},
{'book_id': '22695',
'title': 'Summer Sisters',
'author_id': '12942',
'author': 'Judy Blume',
'position': {'ranking': 970, 'score': 379, 'votes': 4}},
{'book_id': '50877',
'title': 'The Number of the Beast',
'author_id': '205',
'author': 'Robert A. Heinlein',
'position': {'ranking': 971, 'score': 379, 'votes': 4}},
{'book_id': '10941624',
'title': 'Ethereal',
'author_id': '4096668',
'author': 'Addison Moore',
'position': {'ranking': 972, 'score': 379, 'votes': 4}},
{'book_id': '7864437',
'title': 'The Death Cure',
'author_id': '348878',
'author': 'James Dashner',
'position': {'ranking': 973, 'score': 379, 'votes': 4}},
{'book_id': '830',
'title': 'Snow Crash',
'author_id': '545',
'author': 'Neal Stephenson',
'position': {'ranking': 974, 'score': 378, 'votes': 4}},
{'book_id': '11408650',
'title': 'The Unbecoming of Mara Dyer',
'author_id': '4126827',
'author': 'Michelle Hodkin',
'position': {'ranking': 975, 'score': 378, 'votes': 4}},
{'book_id': '5489684',
'title': 'Vampire Kisses: The Beginning',
'author_id': '153734',
'author': 'Ellen Schreiber',
'position': {'ranking': 976, 'score': 377, 'votes': 5}},
{'book_id': '77507',
'title': 'Red Mars',
'author_id': '1858',
'author': 'Kim Stanley Robinson',
'position': {'ranking': 977, 'score': 376, 'votes': 4}},
{'book_id': '246245',
'title': 'The Deerslayer',
'author_id': '9121',
'author': 'James Fenimore Cooper',
'position': {'ranking': 978, 'score': 376, 'votes': 4}},
{'book_id': '11590',
'title': "'Salem's Lot",
'author_id': '3389',
'author': 'Stephen King',
'position': {'ranking': 979, 'score': 376, 'votes': 5}},
{'book_id': '34497',
'title': 'The Color of Magic',
'author_id': '1654',
'author': 'Terry Pratchett',
'position': {'ranking': 980, 'score': 376, 'votes': 4}},
{'book_id': '46544',
'title': 'The Shelters of Stone',
'author_id': '861',
'author': 'Jean M. Auel',
'position': {'ranking': 981, 'score': 375, 'votes': 5}},
{'book_id': '601745',
'title': 'Making Contact with the Other Side: How to Enchance Your Own Psychic Powers',
'author_id': '4333',
'author': 'Sylvia Browne',
'position': {'ranking': 982, 'score': 375, 'votes': 8}},
{'book_id': '44184',
'title': 'Monster',
'author_id': '13291',
'author': 'Walter Dean Myers',
'position': {'ranking': 983, 'score': 374, 'votes': 4}},
{'book_id': '28186',
'title': 'The Sea of Monsters',
'author_id': '15872',
'author': 'Rick Riordan',
'position': {'ranking': 984, 'score': 374, 'votes': 4}},
{'book_id': '469571',
'title': 'All the Pretty Horses',
'author_id': '4178',
'author': 'Cormac McCarthy',
'position': {'ranking': 985, 'score': 374, 'votes': 4}},
{'book_id': '79379',
'title': 'Violets Are Blue',
'author_id': '3780',
'author': 'James Patterson',
'position': {'ranking': 986, 'score': 373, 'votes': 6}},
{'book_id': '15924',
'title': 'At First Sight',
'author_id': '2345',
'author': 'Nicholas Sparks',
'position': {'ranking': 987, 'score': 373, 'votes': 4}},
{'book_id': '6442769',
'title': 'Paper Towns',
'author_id': '1406384',
'author': 'John Green',
'position': {'ranking': 988, 'score': 373, 'votes': 5}},
{'book_id': '86172',
'title': 'A Man in Full',
'author_id': '3083854',
'author': 'Tom Wolfe',
'position': {'ranking': 989, 'score': 372, 'votes': 6}},
{'book_id': '28862',
'title': 'The Prince',
'author_id': '16201',
'author': 'Niccolò Machiavelli',
'position': {'ranking': 990, 'score': 372, 'votes': 5}},
{'book_id': '554798',
'title': 'The Official Pokemon Handbook',
'author_id': '347488',
'author': 'Maria S. Barbo',
'position': {'ranking': 991, 'score': 371, 'votes': 6}},
{'book_id': '5960207',
'title': 'Mr. & Mrs. Fitzwilliam Darcy: Two Shall Become One',
'author_id': '603838',
'author': 'Sharon Lathan',
'position': {'ranking': 992, 'score': 370, 'votes': 4}},
{'book_id': '7673',
'title': 'Eaters of the Dead',
'author_id': '5194',
'author': 'Michael Crichton',
'position': {'ranking': 993, 'score': 369, 'votes': 5}},
{'book_id': '18412',
'title': 'The Wind Done Gone',
'author_id': '11087',
'author': 'Alice Randall',
'position': {'ranking': 994, 'score': 369, 'votes': 4}},
{'book_id': '4008',
'title': 'The Devil and Miss Prym',
'author_id': '566',
'author': 'Paulo Coelho',
'position': {'ranking': 995, 'score': 368, 'votes': 4}},
{'book_id': '109513',
'title': 'The Phantom of Manhattan',
'author_id': '36714',
'author': 'Frederick Forsyth',
'position': {'ranking': 996, 'score': 368, 'votes': 4}},
{'book_id': '6381205',
'title': 'Soulless',
'author_id': '2891665',
'author': 'Gail Carriger',
'position': {'ranking': 997, 'score': 367, 'votes': 4}},
{'book_id': '6391',
'title': 'Christmas in Heaven',
'author_id': '4333',
'author': 'Sylvia Browne',
'position': {'ranking': 998, 'score': 366, 'votes': 6}},
{'book_id': '117376',
'title': 'Rush Hudson Limbaugh and His Times: Reflections on a Life Well Lived',
'author_id': '19794',
'author': 'Rush Limbaugh',
'position': {'ranking': 999, 'score': 366, 'votes': 9}},
{'book_id': '6936382',
'title': 'Anna and the French Kiss',
'author_id': '3095893',
'author': 'Stephanie Perkins',
'position': {'ranking': 1000, 'score': 365, 'votes': 4}},
...]
def check_book_id(book_id):
return 1 if book_id in int_book_ids else 0
value2 = booko3.loc[0, 'books']#extract the column books from the row worst books of all time
chunksize= 10**4
chunks=[]
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize, lines=True):
chunk['id'] = pd.to_numeric(chunk['id'])
chunk['num_pages'] = pd.to_numeric(chunk['num_pages'])
chunk = chunk.dropna(subset=['id', 'num_pages'])#drop rows, that contain an empty string either for 'id' or 'num_pages'
chunks.append(chunk[['id', 'num_pages']])#Only keep the columns 'id' and 'num_pages'
df = pd.concat(chunks, axis=0)#create a new dataframe only containig the stuff that was kept from the chunks
book_ids = [d['book_id'] for d in value2]#Make a list of the book_ids
int_book_ids = list(map(int, book_ids))# make integers of the book_ids
df['sino'] = df['id'].apply(check_book_id)#call the function check_book_id on every element of the list and store either 1 or 0 in a new column 'sino'
filtered_df = df[df['num_pages'] > 700] # Select only the books with more than 700 pages
filtered_df2 = df[(df['num_pages'] > 700) & (df['sino'] == 1)]# select the books with more than 700 pages and are contained in the 'worst books of all time' list
prob= len(filtered_df2)/len(filtered_df)
print(prob)
0.0019798416126709864
Question 4
#Are the events X=’Being Included in The Worst Books of All Time list’ and Y=’Having more than 700 pages’ independent? Explain how you have obtained your answer.
# We will do a chi- square test on idependence to check whether they are independent or not
import json
import pandas as pd
import scipy.stats as stats
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
booko2= pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", nrows=10, lines= True)
booko3=pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/archive/list.json/list.json", nrows=10, lines=True)
#var1= Being included in the Worst Books of All Time list, ##code extracted from 7.3
value2 = booko3.loc[0, 'books']
def check_book_id(book_id):
return 1 if book_id in int_book_ids else 0
chunksize= 10**4
chunks=[]
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize, lines=True):
chunk['id'] = pd.to_numeric(chunk['id'])
chunk['num_pages'] = pd.to_numeric(chunk['num_pages'])
chunk = chunk.dropna(subset=['id', 'num_pages'])
chunks.append(chunk[['id', 'num_pages']])
df = pd.concat(chunks, axis=0)
book_ids = [d['book_id'] for d in value2]
int_book_ids = list(map(int, book_ids))
df['sino'] = df['id'].apply(check_book_id)
#var2= Having more than 700 pages
def check_700(num_pages):
return 1 if num_pages>700 else 0
df['si700'] = df['num_pages'].apply(check_700)# calls function for every row on the column 'num_pages' and stores either 0 or one in the new column 'si700'
contingency_table = pd.crosstab(df['sino'], df['si700'])
chi2, p, dof, expected = stats.chi2_contingency(contingency_table)
print(p)
3.092149285282895e-06
#As the result is smaller than 0.05 we can conclude that the two variables are dependent
Question 1
import json
import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
import numpy as np
chunksize = 10 ** 4
chunks = []
#chunking and data cleaning
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize, lines=True):
chunk['average_rating'].replace('', np.nan, inplace=True)
chunk['num_pages'].replace('', np.nan, inplace=True)
chunk['average_rating'].replace(0.00, np.nan, inplace=True)
chunk['num_pages'].replace(0, np.nan, inplace=True)
chunk['average_rating'] = pd.to_numeric(chunk['average_rating'])
chunk['num_pages'] = pd.to_numeric(chunk['num_pages'])
chunk = chunk.dropna(subset=['average_rating', 'num_pages'])
chunks.append(chunk[['average_rating', 'num_pages']])
#creating a dataframe
df = pd.concat(chunks, axis=0)
correlation = df['average_rating'].corr(df['num_pages'])
print(correlation)
-0.00031640662915722207
The coefficient is slightly smaller than 0, indicating that there is no correlation between the length of a book and the rating.The longest books are not usually rated the worst. As the correlation is even negative, it would rather be the opposite.
Question 2
import json
import pandas as pd
from scipy.stats import ttest_ind
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
import matplotlib.pyplot as plt
import numpy as np
chunks=[]
chunksize=10**4
nrows = 10**3
#chunking and data cleaning
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize, lines=True):
chunk = chunk[['average_rating', 'language']]
chunk['language'].replace('', np.nan, inplace=True)
chunk['average_rating'].replace('', np.nan, inplace=True)
chunk['average_rating'].replace(0.00, np.nan, inplace=True)
chunk.dropna(subset=['language'], inplace=True)
chunk.dropna(subset=['average_rating'], inplace=True)
chunk['average_rating']= pd.to_numeric(chunk['average_rating'])
chunks.append(chunk)
#Creating dataframe
chunks = pd.concat(chunks, axis=0)
#Creting a new column that is 1 for english books and 0 for nonenglish books
chunks['is_english']= chunks['language'].apply(lambda x: int( x[:3] in ['en','eng',"en-"]))
#Create groups for t-test and doing t-test
english_books= chunks[chunks['is_english'] ==1]
non_english_books= chunks[chunks['is_english'] ==0]
t_stat, p_val = ttest_ind(english_books['average_rating'], non_english_books['average_rating'])
print(p_val)
0.0
The p-value is very low, lower than the often used significance value of 0.05. This means, that the average rate distribution of english and non-english books isn't siginificantly different
To further illustrate this we also plotted the average rate distribution for english and nonenglish books in histograms
# Histogram for english books
plt.hist(english_books['average_rating'], alpha=0.8, label='English')
(array([ 2587., 833., 6952., 7825., 18804., 128658., 381247.,
599300., 229201., 81415.]),
array([1. , 1.4, 1.8, 2.2, 2.6, 3. , 3.4, 3.8, 4.2, 4.6, 5. ]),
<BarContainer object of 10 artists>)
# Histogram for non-english books
plt.hist(non_english_books['average_rating'], alpha=0.5, label='Non_English')
(array([ 1897., 715., 6859., 8003., 18997., 115380., 302100.,
452833., 159666., 36380.]),
array([1. , 1.4, 1.8, 2.2, 2.6, 3. , 3.4, 3.8, 4.2, 4.6, 5. ]),
<BarContainer object of 10 artists>)
The two Histograms illustrate that there is no significant difference in the average rate distribution of english and non-english books
Question 3
#Defining variables for the boxplot
ratings_english = english_books['average_rating'].tolist()
ratings_non_english = non_english_books['average_rating'].tolist()
#Creating the boxplot
plt.boxplot([ratings_english, ratings_non_english], labels=['english', 'non-english'])
plt.title('Comparison of average rates')
plt.ylabel('Rate')
plt.show()
#Calculating the means
mean_english = english_books['average_rating'].mean()
mean_non_english = non_english_books['average_rating'].mean()
print('Mean english books: %.3f' % mean_english)
print('Mean non-english books: %.3f' % mean_non_english)
Mean english books: 3.895 Mean non-english books: 3.839
The two means are really close to each other. The mean isn't shown in a boxplot. If the data is perfectly symmetric, the mean is identical with the median
#Calculating the median
median_english = english_books['average_rating'].median()
median_non_english = non_english_books['average_rating'].median()
print('Median english books: %.3f' % median_english)
print('Median non-english books: %.3f' % median_non_english)
Median english books: 3.920 Median non-english books: 3.890
The medians of english and non-english books are really close to each other. The median is the yellow line in the boxplot. Half of the average rates are above the line and half below it. In a boxplot the median is important to show the skewness of the data. As the median for both english and non-english books is more or less in the middle of the box, we can conclude that are data is symmetric.
#Calculating the mode
mode_english = english_books['average_rating'].mode()
mode_non_english = non_english_books['average_rating'].mode()
print('Mode english books: %.3f' % mode_english)
print('Mode non-english books: %.3f' % mode_non_english)
Mode english books: 4.000 Mode non-english books: 4.000
The mode isn't shown in a boxplot, but if the boxplot is perfectly symmetric it is identical with the mean and average.
#Calculating the quartiles
q1_english = english_books['average_rating'].quantile(0.25)
q2_english = english_books['average_rating'].quantile(0.5)
q3_english = english_books['average_rating'].quantile(0.75)
q1_non_english = non_english_books['average_rating'].quantile(0.25)
q2_non_english = non_english_books['average_rating'].quantile(0.5)
q3_non_english = non_english_books['average_rating'].quantile(0.75)
print('Q1 english books: %.3f' % q1_english)
print('Q2 english books: %.3f' % q2_english)
print('Q3 english books: %.3f' % q3_english)
print('Q1 non-english books: %.3f' % q1_non_english)
print('Q2 non-english books: %.3f' % q2_non_english)
print('Q3 non-english books: %.3f' % q3_non_english)
Q1 english books: 3.670 Q2 english books: 3.920 Q3 english books: 4.150 Q1 non-english books: 3.620 Q2 non-english books: 3.890 Q3 non-english books: 4.110
For both english and non-english books, the interquartile range(Q3-Q1) is quite small. This means that our data isn't really dispersed. The interqaurtile range is visualized by the length of the boxplot.
Question 4
import json
import pandas as pd
import statsmodels.api as sm
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import pearsonr
chunksize=10**4
chunks=[]
#chunking and data cleaning
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_authors.json", chunksize=chunksize, lines=True):
chunk = chunk[['fans_count', 'text_reviews_count']]
chunk['text_reviews_count'].replace('', np.nan, inplace=True)
chunk['fans_count'].replace('', np.nan, inplace=True)
chunk.dropna(subset=['text_reviews_count'], inplace=True)
chunk.dropna(subset=['fans_count'], inplace=True)
chunk['text_reviews_count']= pd.to_numeric(chunk['text_reviews_count'])
chunk['fans_count']= pd.to_numeric(chunk['fans_count'])
chunks.append(chunk)
#Creating a new dataframe
chunks = pd.concat(chunks, axis=0)
#Creating variables for the Pearsons Correlation
fans = chunks['fans_count']
reviews = chunks['text_reviews_count']
#Calculating the Pearsons Correlation
correlation, _ = pearsonr(fans, reviews)
print('Pearsons correlation: %.3f' % correlation)
Pearsons correlation: 0.694
The coefficient of 0.694 indicates a positive correlation. The more fans you have, the more reviews you will get.
Question 5
Hypothesis testing is usually done by formulating a null hypothesis, which states that their either is a certain relationship between variables or not. In a second step the prediction of the hypothesis is tested by observing data, which leads to a rejection or acceptance of the null hypothesis. The tests used for hypothesis testing can be divded in two groups: Parametric and nonparametric tests. The main difference between these kind of tests is that parametric tests make certain assumptions about the data (e.g. normally distributed, same variance, sampled randomly), while nonparametric tests don't do that and are more factual. Further for parametric tests the sample size needs to be bigger. We chose parametric tests as they can be computed and interpreted easier than nonparametric tests and we didn't see any of the assumptions about the data as violated.
1.
Select one alternative library to Pandas (i.e., Dask, Polar, Vaex, Datatable etc.), upload authors.json dataset, and filter authors with at least 100 reviews. Do the same using Pandas and compare performance in terms of milliseconds.
!pip install dask
Requirement already satisfied: dask in /usr/local/lib/python3.10/dist-packages (2023.8.1) Requirement already satisfied: click>=8.0 in /usr/local/lib/python3.10/dist-packages (from dask) (8.1.7) Requirement already satisfied: cloudpickle>=1.5.0 in /usr/local/lib/python3.10/dist-packages (from dask) (2.2.1) Requirement already satisfied: fsspec>=2021.09.0 in /usr/local/lib/python3.10/dist-packages (from dask) (2023.6.0) Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from dask) (23.2) Requirement already satisfied: partd>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from dask) (1.4.1) Requirement already satisfied: pyyaml>=5.3.1 in /usr/local/lib/python3.10/dist-packages (from dask) (6.0.1) Requirement already satisfied: toolz>=0.10.0 in /usr/local/lib/python3.10/dist-packages (from dask) (0.12.0) Requirement already satisfied: importlib-metadata>=4.13.0 in /usr/local/lib/python3.10/dist-packages (from dask) (6.8.0) Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata>=4.13.0->dask) (3.17.0) Requirement already satisfied: locket in /usr/local/lib/python3.10/dist-packages (from partd>=1.2.0->dask) (1.0.0)
# Load data using Pandas
start_time = time.time()
pandas_df = pd.read_json(authors_set, lines=True)
# Filter authors with at least 100 reviews
author_counts = pandas_df['name'].value_counts()
authors_with_100_reviews = author_counts[author_counts >= 100].index
filtered_pandas = pandas_df[pandas_df['name'].isin(authors_with_100_reviews)]
pandas_time = (time.time() - start_time) * 1000 # Convert to milliseconds
print("Pandas time (ms):", pandas_time)
Pandas time (ms): 24993.821382522583
import dask.dataframe as dd
import dask
# Load data using Dask
start_time = time.time()
dask_df = dd.read_json(authors_set,lines=True)
# Filter authors with at least 100 reviews
author_counts = dask_df['name'].value_counts()
authors_with_100_reviews = author_counts[author_counts >= 100].compute()
filtered_dask = dask_df[dask_df['name'].isin(authors_with_100_reviews)]
dask_time = (time.time() - start_time) * 1000 # Convert to milliseconds
print("Dask time (ms):", dask_time)
Dask time (ms): 36796.88239097595
As we can see that implementing the task with pandas takes less time than its alternative called DASK. The direct implementation same as pandas gives the above result, though the dask provides the distributed computing services so as to divide the work into number of workers , the later might work effectively interms of time complexity.
#!/bin/bash
echo "id|title|total_books_count"
jq -r '. as $parent | .works[] | [$parent.id, $parent.title, .books_count] | join("|")' series.json | awk -F'|' '{a[$1"|"$2]+=$3} END{for (i in a) print i"| "a[i]}' | sort -t'|' -k3nr | head -5
#!/bin/bash
echo "id|title|total_books_count"
jq -r '. as $parent | .works[] | [$parent.id, $parent.title, .books_count] | join("|")' series.json | awk -F'|' '{a[$1"|"$2]+=$3} END{for (i in a) print i"| "a[i]}' | sort -t'|' -k3nr | head -5
---> Upon implementation the above solution was given based on the fact that the robustness is defined on various factors, including code readability, ease of maintenance, and specific project requirements. Also one different solution was given which handles error and exception if the input file is not present but it was more than three lines of script.
from google.colab import drive
drive.mount('/content/drive')
%cd /content/drive/MyDrive/HW2
Mounted at /content/drive /content/drive/MyDrive/HW2
import pandas as pd
import time
#we store the start time of the script.
start_time= time.time()
#we initialise an empty list
tags_list = []
# we take a chunk size
chunk_size = 20000
# we initialize an empty list to store chunks
lists = pd.DataFrame()
# We Loop through each chunk and append it to the result dataframe
with open('list.json', 'r') as lists_set:
for chunk in pd.read_json(lists_set, lines=True, chunksize=chunk_size):
# We have to Flatten the lists of tags and extend the tags_list
for tags in chunk['tags']:
if isinstance(tags, list):
tags_list.extend(tags)
tags_df = pd.DataFrame({'tags': tags_list})
tags_df.dropna(inplace=True)
# We now will count the usage of each tag
tag_counts = tags_df['tags'].value_counts().reset_index()
tag_counts.columns = ['tag', '#usage']
# We will Sort the DataFrame by usage count in descending order
sorted_tags = tag_counts.sort_values(by='#usage', ascending=False)
end_time= time.time()
# then we print the top tags and time taken
print(sorted_tags.head(5))
print(f"Time taken: {end_time - start_time:.2f} seconds")
tag #usage 0 romance 6001 1 fiction 5291 2 young-adult 5016 3 fantasy 3666 4 science-fiction 2779 Time taken: 74.91 seconds
I have used this as a script file in the name of aws_solution.py and have run the script from the command line. This is the attached screenshot below:
As evident from the screenshot, the result came as expected and took 53.34 seconds in my own macbook.
Then I have created an AWS EC2 instance with the following specifications:
t3.large, volume=30giB
Then I copied the AWS folder containing the necessary files from my system to EC2 instance after connecting to it from the command line as in the following screenshots:
Then I run the script commands in the aws ubuntu:
In the EC2 ubuntu, it took 57.29 seconds to run the same script while it took 53.34 seconds in my own macbook.
from collections import deque
# Read the number of instructions
num_instructions = int(input())
# Initialize a deque to represent the bookshelf
bookshelf = deque()
# Process each instruction
for _ in range(num_instructions):
instruction = input().split()
action, book_id = instruction[0], int(instruction[1])
if action == 'L':
# Place the book to the left of the leftmost existing book
bookshelf.appendleft(book_id)
elif action == 'R':
# Place the book to the right of the rightmost existing book
bookshelf.append(book_id)
elif action == '?':
# Calculate the minimum number of books to pop from both sides
left_count = bookshelf.index(book_id)
right_count = len(bookshelf) - left_count - 1
# Print the result
print(min(left_count, right_count))
8 L 75 R 20 R 30 L 11 ? 75 1 L 12 L 15 ? 20 1
2---> According to LLM Chatbot tool :
To analyze the time complexity of the provided code, we can break it down into its main operations:
Looping through the boss's instructions: This operation takes O(n) time, where 'n' is the number of instructions. For each instruction, we perform the following operations: For 'L' or 'R' instructions, we append to the deque, which takes O(1) time. For '?' instructions, we use the index method to find the position of the book, which takes O(k) time, where 'k' is the position of the book in the deque. In the worst case, 'k' could be equal to the length of the deque, making it O(n). Printing the result in each '?' instruction takes O(1) time.
Given these considerations, the overall time complexity of the code is O(n^2) in the worst case, as the worst-case scenario occurs when each '?' instruction has to search through the entire deque, and there are 'n' such instructions. '''
'''We believe the instructions given by the LLM Chatbot tool is correct and upon observation with different input sizes we can see that the most expensive operation in the code is to calculate the ? instructions.'''
3 ---> NO the code provided above is not the optimal code , we can reduce the time complexity of the above code by using a different data structure called dictionary. The time complexity for it can be reduced to O(n)
Algorithm:
Initialize an empty dictionary called book_positions
Initialize an empty list called bookshelf
Read num_instructions
For i in range(num_instructions): Parse the instruction into action and book_id
If action is 'L':
Insert book_id at the beginning of bookshelf
Store the position of book_id in book_positions
If action is 'R':
Append book_id to the end of bookshelf
Store the position of book_id in book_positions
If action is '?':
Retrieve book_id's position from book_positions
Calculate left_count as min(book_id's position, length of bookshelf - book_id's position - 1)
Print left_count
efficient O(1) time complexity for the '?' instructions.